multilocus

Multilocus refers to analyses that use information from more than one genetic locus. In contrast to single-locus approaches, multilocus methods aim to capture a broader view of genetic variation, lineage relationships, and population structure. Data may come from sequence data across several loci, microsatellite markers, or genome-wide single-nucleotide polymorphisms (SNPs). A common application is multilocus sequence typing (MLST), in which fragments of several housekeeping genes are sequenced to assign isolates to sequence types. MLST has inspired broader schemes such as whole-genome multilocus sequence typing (wgMLST) that compare allelic profiles across many loci.

Analytical approaches for multilocus data include concatenation, in which sequences from all loci are combined into a single dataset for phylogenetic inference, and coalescent-based species-tree methods that explicitly model the genealogical histories of individual loci and their discordance due to recombination and incomplete lineage sorting. Multilocus data improve estimates of population structure, demographic history, and species boundaries, and enhance the power of genetic association studies and linkage mapping.

Challenges include recombination among loci, paralogy and locus misassembly, missing data, and ascertainment bias. Proper locus selection, data quality control, and appropriate analytical models are essential. Multilocus strategies are widely used in microbiology for strain typing, in population genetics for inference of evolutionary processes, and in comparative genomics to reconstruct recent and ancient relationships.