MicroRNAs (miRNAs) are one of evolutionary conserved functional non-coding small RNAs with approximately ~24 nucleotides. Because the first draft genome sequence and its annotation for Brassica rapa which is one of the two ancestral species of oilseed rape is currently available, identification of miRNAs and their target prediction in the genome can be explored by comparison with miRNA families in A. thaliana. However computational methods often provide unreliable candidate miRNAs due to lack of gene structure information and genome wide experimental data. For this reason we intend to provide more reliable prediction of B. rapa miRNAs on the genome based on high throughput Illumina small RNA deep-sequencing data. We developed a novel miRNA database of B. rapa, BraMRs, that integrated B. rapa miRNA identification, target prediction, and functional annotation for targets. BraMRs identifies putative miRNAs based on combination of similarity search and Illumina small RNA sequencing data generated from five plant tissues (seedling, root, leaf, stem, and flower). The prediction method consists of various features including genomic sources, secondary structures, and sequence composition. For target prediction, potential target genes were obtained by miRanda program with perfect or near complementary matches. The tool thoroughly searches for potential complementary target sites with mismatches tolerable in miRNA-target recognition and alignment threshold. Function of putative miRNAs is inferred from the list of target genes obtained. Statistical enrichment of target genes is explored in terms of gene ontology, pathway, Pfam domains, and twenty eight-tissue and stress response ESTs annotations.