in assembling fewer reads with a high degree of overlap. De Bruijn graphs align k-mers (usually 25-50 bp) based on k-1 sequence conservation to create contigs. The k-mers are shorter than the read lengths allowing fast hashing so the operations in de Bruijn graphs are generally less computationally intensive. Functional annotation Functional annotation of the assembled transcripts allows for insight into the particular molecular functions, cellular components, and biological processes in which the putative proteins are involved. Blast2GO (B2G) enables Gene Ontology based data mining to annotate sequence data for which no GO annotation is available yet. It is a research tool often employed in functional genomics research on non-model species. It works by blasting assembled contigs against a non-redundant protein database (at NCBI), then annotating them based on sequence similarity. GOanna is another GO annotation program specific for animal and agricultural plant gene products that works in a similar fashion. It is part of the AgBase database of curated, publicly accessible suite of computational tools for GO annotation and analysis. Following annotation, KEGG (Kyoto Encyclopedia of Genes and Genomes) enables visualization of metabolic pathways and molecular interaction networks captured in the transcriptome. In addition to being annotated for GO terms, contigs can also be screened for open reading frames (ORFs) in order to predict the amino acid sequence of proteins derived from these transcripts. Another approach is to annotate protein domains and determine the presence of gene families, rather than specific genes. Verification and quality control Since a well-resolved reference genome is rarely available, the quality of computer-assembled contigs may be verified either by comparing the assembled sequences to the reads used to generate them (reference-free), or by aligning the sequences of conserved gene domains found in mRNA transcripts to transcriptomes or genomes of closely related species (reference-based). Tools such as Transrate and DETONATE allow statistical analysis of assembly quality by these methods. Another method is to design PCR primers for predicted transcripts, then attempt to amplify them from the cDNA library. Often, exceptionally short reads are filtered out. Short sequences (< 40 amino acids) are unlikely to represent functional proteins, as they are unable to fold independently and form hydrophobic cores. Complementary to these metrics, a quantitative assessment of the gene content may provide additional insights into the quality of the assembly. To perform this step, tools that model the expected gene space based of conserved genes, such