Several studies have documented the genetic effects of intraspecific hybridization of cultured and wild Atlantic salmon (Salmo salar L.). However, the effect of salmon aquaculture on wild congeners is not so well understood. Diseases, introduced or increased in incidence by salmon aquaculture activities, may have an impact on co-occurring wild sea trout (Salmo trutta L.), as implied by the steep decline in sea trout numbers in many Irish, Scottish, and Norwegian rivers since the late 1980s, which may be linked to sea lice infestations associated with marine salmonid farming. Our data suggest that salmon farming and ocean ranching can indirectly affect, most likely mediated by disease, the genetics of cohabiting sea trout by reducing variability at major histocompatibility class I genes. We studied samples of DNA extracted from scales of sea trout in the Burrishoole River, in the west of Ireland, before and at intervals during aquaculture activities. In these samples, allelic variation at a microsatellite marker, tightly linked to a locus critical to immune response (Satr-UBA), was compared with variation at six neutral microsatellite loci. A significant decline in allelic richness and gene diversity at the Satr-UBA marker locus, observed since aquaculture started and which may indicate a selective response, was not reflected by similar reductions at neutral loci. Subsequent recovery of variability at the Satr-UBA marker, seen among later samples, may reflect an increased contribution by resident brown trout to the remaining sea trout stock.

Microbial genotyping increasingly deals with large numbers of samples, and data are commonly evaluated by unstructured approaches, such as spread-sheets. The efficiency, reliability and throughput of genotyping would benefit from the automation of manual manipulations within the context of sophisticated data storage. We developed a medium- throughput genotyping pipeline for MultiLocus Sequence Typing (MLST) of bacterial pathogens. This pipeline was implemented through a combination of four automated liquid handling systems, a Laboratory Information Management System (LIMS) consisting of a variety of dedicated commercial operating systems and programs, including a Sample Management System, plus numerous Python scripts. All tubes and microwell racks were bar-coded and their locations and status were recorded in the LIMS. We also created a hierarchical set of items that could be used to represent bacterial species, their products and experiments. The LIMS allowed reliable, semi-automated, traceable bacterial genotyping from initial single colony isolation and sub-cultivation through DNA extraction and normalization to PCRs, sequencing and MLST sequence trace evaluation. We also describe robotic sequencing to facilitate cherrypicking of sequence dropouts. This pipeline is user-friendly, with a throughput of 96 strains within 10 working days at a total cost of < €25 per strain. Since developing this pipeline, >200,000 items were processed by two to three people. Our sophisticated automated pipeline can be implemented by a small microbiology group without extensive external support, and provides a general framework for semi-automated bacterial genotyping of large numbers of samples at low cost.

Major histocompatibility complex (MHC) class I-linked microsatellite data and parental assignment data for a group of wild brown trout (Salmo trutta L.) provide evidence of closer spatial aggregation among fry sharing greater numbers of MHC class I alleles under natural conditions. This result confirms predictions from laboratory experiments demonstrating a hierarchical preference for association of fry sharing MHC alleles. Full-siblings emerge from the same nest (redd), and a passive kin association pattern arising from limited dispersal from the nest (redd effect) would predict that all such pairs would have a similar distribution. However, this study demonstrates a strong, significant trend for reduced distance between pairs of full-sibling fry sharing more MHC class I alleles reflecting their closer aggregation (no alleles shared, 311.5 ± (s.e.)21.03 m; one allele shared, 222.2 ± 14.49 m; two alleles shared, 124.9 ± 23.88 m; P<0.0001). A significant trend for closer aggregation among fry sharing more MHC class I alleles was also observed in fry pairs, which were known to have different mothers and were otherwise unrelated (ML-r = 0) (no alleles: 457.6 ± 3.58 m; one allele (422.4 ± 3.86 m); two alleles (381.7 ± 10.72 m); P<0.0001). These pairs are expected to have emerged from different redds and a passive association would then be unlikely. These data suggest that sharing MHC class I alleles has a role in maintaining kin association among full-siblings after emergence. This study demonstrates a pattern consistent with MHC-mediated kin association in the wild for the first time.

We tested how variation at a gene of adaptive importance, MHC class I (UBA), in a wild, endemic Salmo trutta population compared to that in both a previously studied non-native S. trutta population and a co-habiting Salmo salar population (a sister species). High allelic diversity is observed and allelic divergence is much higher than that noted previously for co-habiting S. salar. Recombination was found to be important to population-level divergence. The α1 and α2 domains of UBA demonstrate ancient lineages but novel lineages are also identified at both domains in this work. We also find examples of recombination between UBA and the non-classical locus, ULA. Evidence for strong diversifying selection was found at a discrete suite of S. trutta UBA amino acid sites. The pattern was found to contrast with that found in re-analysed UBA data from an artificially stocked S. trutta population.

Evidence is reported for balancing selection acting on variation at major histocompatibility complex (MHC) in wild populations of brown trout Salmo trutta. First, variation at an MHC class I (satr‐uba)–linked microsatellite locus (mhc1) is retained in small S. trutta populations isolated above waterfalls although variation is lost at neutral microsatellite markers. Second, populations across several catchments are less differentiated at mhc1 than at neutral markers, as predicted by theory. The population structure of these fish was also elucidated.