Atherosclerosis is a transmural chronic inflammatory condition of small and large arteries that is associated with adaptive immune responses at all disease stages. However, impacts of adaptive immune reactions on clinically apparent atherosclerosis such as intima lesion (plaque) rupture, thrombosis, myocardial infarction, and aneurysm largely remain to be identified. It is increasingly recognized that leukocyte infiltrates in plaque, media, and adventitia are distinct but that their specific roles have not been defined. To map these infiltrates, we employed laser-capture microdissection (LCM) to isolate the three arterial wall laminae using apoE⁻/⁻ mouse aorta as a model. RNA from LCM-separated tissues was extracted and large-scale, whole-genome expression microarrays were prepared. We observed that the quality of the resulting gene expression maps was compromised by tissue RNA carried over from adjacent laminae during LCM. To account for these flaws, we established quality controls and algorithms to improve the predictive power of LCM-derived microarray data. Our approach creates robust transcriptome atlases of normal and atherosclerotic aorta. Assessing LCM transcriptomes for immunity-related mRNAs indicated markedly distinctive gene expression patterns in the three laminae of the atherosclerotic aorta. These mouse mRNA expression data banks can now be mined to address a wide range of questions in cardiovascular biology.