DOI: 10.5061/dryad.xsj3tx9fg
title: Archived data for: Balancing selection, genetic drift, and human mediated-introgression interplay to shape MHC (functional) diversity in Mediterranean brown trout

description: The extraordinary polymorphism of Major Histocompatibility Complex (MHC)
 genes is considered a paradigm of pathogen-mediated balancing selection,
 although empirical evidence is still scarce. Furthermore, the relative
 contribution of balancing selection to shape MHC population structure and
 diversity, compared to that of neutral forces, as well as its interaction
 with other evolutionary processes such as hybridization, remains largely
 unclear. To investigate these issues, we analysed adaptive (MHC-DAB gene)
 and neutral (11 microsatellite loci) variation in 156 brown trout (Salmo
 trutta complex) from six wild populations in central Italy exposed to
 introgression from domestic hatchery lineages (assessed with the LDH
 gene). MHC diversity and structuring correlated with those at
 microsatellites, indicating the substantial role of neutral forces.
 However, individuals carrying locally rare MHC alleles/supertypes
 (regardless of the zygosity status and degree of sequence dissimilarity of
 MHC) were in better body condition (a proxy of individual fitness/parasite
 load), hence supporting balancing selection under rare allele advantage,
 but not heterozygote advantage or divergent allele advantage. The
 association between specific MHC supertypes and body condition confirmed
 in part this finding. Across populations, MHC allelic richness increased
 with increasing admixture between native and domestic lineages, indicating
 introgression as a source of MHC variation. Furthermore, introgression
 across populations appeared more pronounced for MHC than microsatellites,
 possibly because initially-rare MHC variants are expected to introgress
 more readily under rare allele advantage. Providing evidence for the
 complex interplay among neutral evolutionary forces, balancing selection
 and human-mediated introgression in shaping the pattern of MHC
 (functional) variation, our findings contribute to a deeper understanding
 of the evolution of MHC genes in wild populations exposed to anthropogenic
 disturbance.
description: 1. Filename:<b>
 </b>“<b>Brown_trout_MHC_fastq_paired</b>”
 (folder) Paired-end Fastq files (*.R1 and
 *.R2) from Illumina MiSeq 2x300 bp run: 15 batches, each contains barcoded
 MHC-DAB amplicons of 6-19 Mediterranean brown trout individuals as
 specified in “Brown_trout_amplicon_data-batches.txt”) 2.
 Filename:
 “<b>Brown_trout_amplicon_data-batches.txt</b>” Individual dual-tag and batch
 membership of overall 156 Mediterranean brown trout samples. Each batch
 (overall 15) contains from 6 to 19 barcoded amplicons. 3. Filename:<b>
 </b>“<b>MHC-DAB_genotypes_AmpliSAS.xlsx</b>”
 The AmpliSAS output file
 containing individual MHC-DAB alleles and their coverage for 156
 Mediterranean brown trout samples. The following information is provided
 for each individual: the overall number of reads (DEPTH_AMPLICON); the
 overall number of allele reads (DEPTH_ALLELES); the number of alleles
 (COUNT_ALLELE); the number of reads for each allele. The following
 information is provided for each of 58 MHC-DAB alleles: the nucleotide
 sequence (SEQUENCE); the sequence length (LENGTH); the overall number of
 reads (DEPTH) the number of individuals carrying that allele (SAMPLES);
 allele code (ALLELE); the average within-individual reads (MEAN_FREQ); the
 maximum (MAX_FREQ) and minimum (MIN_FREQ) frequency of reads observed
 within an individual. 4. Filename:
 “<b>MHC&STR_genotypes.xlsx</b>” Individual genotypes of 11
 microsatellite loci, the MHC-DAB, and MHC-ST (supertypes). Data are in
 GenAlEx 6.5 format. Note that MHC-DAB*c, *e, *g, *k and *l alleles are
 coded as 501, 502, 503, 504 and 505 respectively. 5. Filename:
 “<b>phenotypic&genetic_data.csv</b>” Phenotypic and genetic data of
 156 Mediterranean brown trout used for testing the association between MHC
 and body condition. The following individual data are provided: name
 (Sample); origin (Pop); Fulton’s body condition factor (BC); LDH-C1
 genotype (LDH: native = 100/100, hybrid = 90/100, domestic = 90/90); mean
 heterozygosity computed over 11 microsatellite loci (H); genetic
 dissimilarity between MHC alleles computed as Kimura 2-parameter
 nucleotide distance (K2P_dist) and Poisson-corrected amino acid distance
 (Poi_dist); MHC-DAB genotype (DAB1 and DAB2); genotype based on
 MHC-supertypes (ST1 and ST2); within-population frequency of MHC-DAB
 allele 1 and 2 (freq_DAB1 and freq_DAB2); within-population frequency of
 supertype 1 and 2 (freq_ST1 and freq_ST2). Note that MHC-DAB*c, *e, *g, *k
 and *l alleles are coded as 501, 502, 503, 504 and 505
 respectively. 6.
 Filename: “<b>Randomize_supertypes.R</b>” R-script to iteratively assign
 MHC alleles to supertypes at random and calculate per-population
 differentiation (Nei’s G<sub>ST</sub>, Hedrick’s
 G<sub>ST</sub> and Jost’s D) following the randomization
 approach described in Lighten et al. (2017). The script also generates a
 plot of observed versus simulated population differentiation, along with
 Holm-Bonferroni corrected p-values. Note that you may run the
 randomization analysis with our published MHC data by using the
 “phenotypic&genetic_data.csv” as input file.<b>
 </b> 7.
 Filename: “<b>Appendices_R1_final.docx</b>” Manuscript’s supplementary
 information: 10 Appendices