Rapid developmentsinmolecular biology coupled with progress in biocomputing are empowering more and more biologists in their research, particularly geneticists. The processing of data from high-density DNA microarrays is now possible for most users and autozygosity mapping is a widely used method for the identification of recessively inherited disease genes using small consanguineous families. With the popular technique of exome sequencing, it is important to consider the possibility of concurrently defining autozygous regions and identifying possibly deleterious sequence variants, using data from a single sequencing experiment.
Carr et al. (Hum Mutat 34:50–56, 2013) have developed two programs that rapidly identify autozygous regions using whole exome sequence data. These applications can identify all possibly deleterious sequence variants within autozygous intervals. AgileVariantMapper uses genotypes of all positions found ab initio to be polymorphic by the analysis of exome sequence data, while AgileGenotyper deduces genotypes at over 0.5 million exonic positions found to be polymorphic in the 1000 Genomes Project data set. These programs derive their genotyping data either by the detection of all sequence variants or by the assessment of 0.53 million known polymorphic positions within each exome dataset. Using genotype data derived solely from exome sequencing, it is possible to identify the majority of autozygous regions found also by SNP microarray genotype data.
The authors acknowledge factors that might complicate analysis with these tools, including low read depth, uneven coding sequence distribution, or the existence of duplicated sequences that could interfere with the genotyping process. That said, the programs are clearly useful for allowing investigators to successfully use exome-based autozygosity mapping, while high-density microarrays could be necessary for precise delineation of autozygous regions, in particular very small ones.