Differences in gene expression underlie central questions in plant biology extending from gene function to evolutionary mechanisms and quantitative traits. However, resolving expression of closely related genes (e.g. alleles and gene family members) is challenging on a genome-wide scale due to extensive sequence similarity and frequently incomplete genome sequence data. We present a new expression-profiling strategy that utilizes long-read, high-throughput sequencing to capture the information-rich 3'-untranslated region (UTR) of messenger RNAs (mRNAs). Resulting sequences resolve gene-specific transcripts independent of a sequenced genome. Analysis of approximately 229,000 3'-anchored sequences from maize (Zea mays) ovaries identified 14,822 unique transcripts represented by at least two sequence reads. Total RNA from ovaries of drought-stressed wild-type and viviparous-1 mutant plants was used to construct a multiplex cDNA library. Each sample was labeled by incorporating one of 16 unique three-base key codes into the 3'-cDNA fragments, and combined samples were sequenced using a GS 20 454 instrument. Transcript abundance was quantified by frequency of sequences identifying each unique mRNA. At least 202 unique transcripts showed highly significant differences in abundance between wild-type and mutant samples. For a subset of mRNAs, quantitative differences were validated by real-time reverse transcription-polymerase chain reaction. The 3'-UTR profile resolved 12 unique cellulose synthase (CesA) transcripts in maize ovaries and identified previously uncharacterized members of a histone H1 gene family. In addition, this method resolved nearly identical paralogs, as illustrated by two auxin-repressed, dormancy-associated (Arda) transcripts, which showed reciprocal mRNA abundance in wild-type and mutant samples. Our results demonstrate the potential of 3'-UTR profiling for resolving gene- and allele-specific transcripts.