For a quick (but reliable) analysis, I'd recommend using Kallisto or Salmon to quantify isoform read counts using the transcriptome of the lab strain.
If you have a concern about transcripts that are in your sample but not in the lab strain, you can do two Trinity assemblies: one fully de-novo, and one genome-guided. These transcripts can then be used as a reference assembly for Kallisto/Salmon, and counts compared to the lab-strain results. Note that the Trinity assemblies will only apply to the particular environments that are in your samples; if a transcript isn't expressed, it won't be in the assembly.
Any transcripts in the de-novo assembly that are not in the genome-guided assembly are potentially novel to your strain. However, care must be taken in interpreting this: if there is any other contamination in the sample, those contaminant transcripts will also be assembled.
I'm not too familiar with annotation pipelines, but based on a couple of Twitter posts it looks like Prokka might be a reasonable start. Torsten Seeman (lead developer of Prokka) has done a post about alternative annotation pipelines:
http://thegenomefactory.blogspot.co.nz/2013/03/bacterial-genome-annotation-systems.html
Update: Torsten Seeman now recommends Bakta as a "worthy successor to Prokka":
https://github.com/oschwengers/bakta
Bakta is a tool for the rapid & standardized annotation of bacterial genomes and plasmids from both isolates and MAGs. It provides dbxref-rich, sORF-including and taxon-independent annotations in machine-readable JSON & bioinformatics standard file formats for automated downstream analysis.