To compare gene expression among bovine tissues we used large bovine RNAseq datasets comprising 280 samples from 10 different bovine tissues (uterine endometrium, granulosa cells, theca cells, cervix, embryos, leukocytes, liver, hypothalamus, pituitary, muscle) generating 260 Gbases of data. We used twin approaches of an information-theoretic analysis of the existing annotated transcriptome to identify the most tissue-specific genes, as well as a de-novo transcriptome annotation to evaluate general features of the transcription landscape. We detected expression of 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. We conclude that it is combined effects of the variable expression of large numbers of genes (73 to 93% of the genome) with the specific expression of a small number of genes (less than 1% of the transcriptome) that contributes to determining the outcome of the function of individual tissues.