In this study using RNA-Seq we describe the whole genome transcriptome profile of H. somni 2336, a bovine respiratory disease pathogen. The single nucleotide resolution map helped uncover the structure and complexity of this pathogen's transcriptome and led to the identification of novel, small RNAs and protein coding genes as well as gene co-expression. Prokaryotic genome annotation is performed often using computational gene prediction programs [8, 9] . However, these prediction algorithms are not able to identify the non-coding sRNAs, antisense transcripts, and other small proteins. To overcome the shortcomings of computational genome structural annotation, various experimental methods are used for identification of novel expressed elements [13, 14, 15, 16, 17, 18, 26, 27, 28] . Deep transcriptome sequencing (RNA-Seq) has emerged recently as a method that enables the study of RNA-based structural and regulatory regions at the genome scale. RNA-Seq technology has many advantages compared with existing array based methods for transcriptome analysis. In particular, RNA-Seq does not require probes, so the process is free from probe design issues or bias from hybridization issues. Also, the transcriptome coverage from RNA-Seq is very high [29, 30] . RNA-Seq was demonstrated to be effective for the discovery of bacterial non-coding RNAs, accurate operon definition, and correction of gene annotation [27, 31, 32] . Therefore, in the current study, we used RNA-Seq for profiling H. somni 2336 transcriptome.