NextGen sequencing technologies offer new strategies to simultaneously map key traits and identify underlying candidate genes. To date, emphasis has been placed on re-sequencing numerous individual genomes for association genetics. While robust, this method is costly and requires extensive computational capacity. Here we show that a smaller number of pooled genomes (dubbed pnomes) can be used to map and identify specific candidate genes. We tested the pnomes approach using an F2 population segregating for the peach pillar trait (Br) which shows a columnar growth habit. Br was previously mapped to peach LG2 using standard molecular marker techniques. Genomic DNA was pooled from 27 standard trees (BrBr) and 56 trees exhibiting the pillar architecture (brbr). The two DNA pools were subjected to Illumina GAII 100bp paired-end sequencing. 174 million reads were obtained for the standard pnome and 218 million reads for the pillar pnome giving an estimated coverage of 2X and 1.6X, respectively. Next, the pillar and standard reads were separately assembled against the peach genome using CLC Genomics Workbench Software (CLC Bio, Netherlands). SNPs and DIPs were identified (300,000 in total) and filtered to remove unlinked SNPs/DIPs as well as artifacts arising from assembly errors. After filtering, 487 SNPs and 23 DIPs remained and all were located on Chr2. These were used to create an allele frequency map, revealing the location of the Br trait near position 20.0 Mb; consistent with previous mapping studies. Thus, the pnomes approach provides a robust and relatively inexpensive alternative for candidate gene association studies in peach.