We created an algorithm that allows high-throughput mapping of sense-antisense (SA) pairs of transcripts. By this method we mapped approximately 32 000 SA pairs of human mRNAs. Collected SA pairs were divided into three groups: SA pairs based on two or more UniGene clusters (17% of all sense-antisense pairs), SA pairs based on ESTs that belong to the same UniGene cluster (42%), and SA pairs formed by UniGene cluster and non-unique unclustered transcripts (41%). To study expression patterns of natural SA pairs we created a software application "Antisense Cluster Filter". We retrieved tissue expression data for all the transcripts forming identified SA pairs, including clustered and unclustered ones. After that, we selected 108 SA pairs represented by transcripts differentially regulated in human tumors. For each of these SA pairs one of the transcripts was expressed only in tumors, another one was expressed both in non-malignant and malignant tissues. Indicated SA pairs may represent a new class of tumor markers. An example of the tumor-specific natural antisense to C3orf4 mRNA is detailed.