Genome (re‐)annotation and open‐source annotation pipelines

Abstract

These days, more and more scientists are diving into genome sequencing projects, urged by fast and cheap next‐generation sequencing technologies. Only to discover that they are quickly drowning in an unfathomable sea of sequence data and gasping for help from experts to make biological sense of this ensuing disaster. Bioinformaticians and genome annotators to the rescue! Microbial genome annotation involves primarily identifying the genes (or actually the open reading frames: ORFs) encrypted in the DNA sequence and deducing functionality of the encoded protein and RNA products (Fig. 1). First, a gene finder such as Glimmer (Delcher et al., 1999) or GeneMark (Lukashin and Borodovsky, 1998) is applied to the genome DNA sequence, producing a set of predicted protein‐coding genes. These programs are quite accurate, though not perfect. The next step is to take the set of predictions and search for hits against one or more protein and/or protein domain databases using blast (Altschul et al., 1997), HMMer (Eddy, 1998) or other programs. For each gene that has a significant match, the blast output together with the annotation of the hit can be used to assign a name and function to the protein. The accuracy of this step depends not only on the annotation software, but also on the quality of the annotations already in the reference database. Figure 1 A generalised flow chart of genome annotation. Statistical gene prediction: use of methods like GeneMark or Glimmer to predict protein‐coding genes. General database search: searching sequence databases (typically, NCBI NR) for sequence similarity, ... Genome sequences deposited in NCBI/GenBank, EMBL and DDBJ databases (which mirror each other) are annotated by the submitting groups, who each use their own methods, criteria and thoroughness. This leads to a large diversity in annotation completeness and accuracy. Many of the first genomes published had very limited or no functional annotation, simply because there was very little genomic information in these reference databases to compare with. Most public genome annotation remains static for years, and many annotations have never been changed since their initial publication. Over the years, annotation updates may have been maintained by the submitters, but they are generally only stored in local databases such as GenProtEC/EcoGene for Escherichia coli K12 (Rudd, 2000), Genolist/Bactilist for Bacillus subtilis 168 (Lechat et al., 2008) and SGD for Saccharomyces cerevisiae (Christie et al., 2004). Since gene functional annotation relies heavily on sequence similarity searching techniques with protein sequence databases, automatically annotated entries based on blast hits to NCBI databases can quickly become outdated. In the mean time, downstream sciences, such as comparative genomics, proteomics, transcriptomics and metabolomics, have rapidly increased our knowledge of many gene products. It is critical therefore, that genome annotations are frequently updated if the information they contain is to remain accurate, relevant and useful.