Bioinformatics Approaches for Analyzing Multigene Families Encoding Immune Receptors.

Genome sequences are quickly becoming available from a variety of organisms, providing researchers with an abundance of previously inaccessible information and an important source of insight into immune mechanisms. There are a variety of methods to accurately characterize genes from new genome sequences, but immune receptors pose special challenges for these techniques. Immune receptors, particularly those that directly recognize pathogens, often diverge rapidly among species and are commonly found in large, complex multigene families. Because of these characteristics, immune receptors tend to be overlooked or misannotated in large-scale genomic surveys. We describe here a strategy to characterize homologs of immune receptors and to identify putative receptors from newly assembled genome or transcriptome sequences. The description of these protocols is aimed at a typical immunologist and does not rely on substantial a priori knowledge of bioinformatics. The approach is based on using low-stringency sequence searches to identify divergent homologs. For receptors with multiple domains, the intersection of low-stringency searches can be used to identify divergent receptor sequences with high confidence. For multigene families, these predictions can be refined using sequence conservation among gene family paralogs. Assembled genome sequences serve as a critical foundation for subsequent functional characterization and remove long-standing barriers in understanding the evolution of immune recognition systems.