Using the transcriptome to annotate the genome

A remaining challenge for the human genome project involves the identification and annotation of expressed genes. The public and private sequencing efforts have identified ∼15,000 sequences that meet stringent criteria for genes, such as correspondence with known genes from humans or other species, and have made another ∼10,000–20,000 gene predictions of lower confidence, supported by various types of in silico evidence, including homology studies, domain searches, and ab initio gene predictions 1 , 2 . These computational methods have limitations, both because they are unable to identify a significant fraction of genes and exons and because they are unable to provide definitive evidence about whether a hypothetical gene is actually expressed 3 , 4 . As the in silico approaches identified a smaller number of genes than anticipated 5 , 6 , 7 , 8 , 9 , we wondered whether high-throughput experimental analyses could be used to provide evidence for the expression of hypothetical genes and to reveal previously undiscovered genes. We describe here the development of such a method—called long serial analysis of gene expression (LongSAGE), an adaption of the original SAGE approach 10 —that can be used to rapidly identify novel genes and exons.