Genome-wide DNA microarray analysis of RNA transcript lengths in yeast and man

We developed the "Virtual Northern," a DNA microarray-based method for measuring RNA transcript lengths on a genomic scale. We applied it to both the yeast and human genomes. The genome of the yeast Saccharomyces cerevisiae is small. Its genes are closely spaced, few contain introns, and very few encode multiple transcript variants. In contrast, human genes are widely spaced, nearly all contain numerous introns and most undergo extensive alternative splicing. Although both organisms have been extensively studied, the ease of identifying genes in the yeast genome has led to little characterization of yeast mRNA, and the low density and high complexity of human genes has made obtaining a complete catalog of human genes and the transcript variants they encode difficult.; Virtual Northern analysis of the S. cerevisiae genome yielded a transcript length measurement for 84% of the annotated genes in the yeast genome. We found a close linear relationship between mRNA lengths and the lengths of translated sequences; mRNAs were typically ∼300 nucleotides longer than the translated sequences. Analysis of genes deviating from that relationship assisted in the reannotation of numerous genes. Interestingly, we found that systematic differences in the total length of the untranslated regions (UTRs) in mRNAs were related to the functions of the encoded proteins. Yeast devote a substantial fraction of their genome sequence to the UTRs of their mRNAs (∼12--15%). It is likely that the relationship between UTR length and protein function points to an important regulatory role for these sequences.; We applied the Virtual Northern method to a sample of human brain mRNA and obtained 17,535 mRNA length measurements representing at least 9,151 genes. By comparing the generated mRNA length dataset to the Reference sequence (Refseq) database maintained by the National Center for Biotechnology Information, we found that the majority of length measurements in our dataset correspond to currently uncharacterized transcripts. We found a similar linear relationship between mRNA length and open reading frame (ORF) length in human as we did in yeast. We also found the same relationship between UTR length and protein function, providing further evidence for an important regulatory role of UTRs.