Gene flow, effective population size and selection at major histocompatibility complex genes: brown trout in the Hardanger Fjord, Norway

Abstract

Brown trout populations in the Hardanger Fjord, Norway, have declined drastically due to increased exposure to salmon lice from salmonid aquaculture. We studied contemporary samples from seven populations and historical samples (1972 and 1983) from the two largest populations, one of which has declined drastically whereas the other remains stable. We analysed 11 microsatellite loci, including one tightly linked to the UBA gene of the major histocompatibility class I complex (MHC) and another locus linked to the TAP2A gene, also associated with MHC. The results revealed asymmetric gene flow from the two largest populations to the other, smaller populations. This has important conservation implications, and we predict that possible future population recoveries will be mediated primarily by the remaining large population. Tests for selection suggested diversifying selection at UBA, whereas evidence was inconclusive for TAP2A. There was no evidence for temporally fluctuating selection. We assessed the distribution of adaptive divergence among populations. The results showed the most pronounced footprints of selection between the two largest populations subject to the least immigration. We suggest that asymmetric gene flow has an important influence on adaptive divergence and constrains local adaptive responses in the smaller populations. Even though UBA alleles may not affect salmon louse resistance, the results bear evidence of adaptive divergence among populations at immune system genes. This suggests that similar genetic differences could exist at salmon louse resistance loci, thus rendering it a realistic scenario that differential population declines could reflect differences in adaptive variation.

Demographic and genetic factors shaping contemporary metapopulation effective size and its empirical estimation in salmonid fish

“…It is not known, however, how prevalent such connectivity patterns are in the wild. Based on demography and neutral conditions, one would expect positive density-dependent dispersal, and so far this pattern is supported by empirical genetic analyses (for example, Hansen et al, 2007, but see Palstra et al (2007)). Although our results are most easily explained by a combination of negative density-dependent dispersal and a general upward bias in N e(s) estimates (Figure 4, left), these two requirements may be somewhat mutually exclusive.…”

“…Second, the species has been subject to extensive genetic study (Verspoor et al, 2008) and its spatial and temporal genetic structures are relatively well documented (for example, King et al, 2001;Dionne et al, 2008;Palstra and Ruzzante, 2010). Finally, small populations of Atlantic salmon often maintain surprisingly high levels of genetic diversity, suggesting that gene flow is not negligible and might often be asymmetrical (for example, Østergaard et al, 2003;Consuegra et al, 2005;Hansen et al, 2007;Palstra et al, 2007).…”

Detecting population structure in a high gene-flow species, Atlantic herring (Clupea harengus): direct, simultaneous evaluation of neutral vs putatively selected loci

“…The locus is situated in the third intron of the MH IIA gene, and the extent to which the variability in the microsatellite reflects exonic variability is unknown (Stet et al, 2008). Previous attempts to estimate the variability in MHC genes using embedded micro-or minisatellites in salmonids have yielded varying results Grimholt et al, 2002Grimholt et al, , 2003Hansen et al, 2007;de Eyto et al, 2007). de Eyto et al (2007) found a one-to-one relationship between minisatellite and MH class II allelic variability; however, for MH class I, a specific microsatellite allele could be found in several different MH I alleles.…”

“…For example, disease challenge trials on Atlantic salmon confirm that polymorphism at the MHC genes are associated with increased disease resistance (Grimholt et al, 2003). Wild populations show evidence for local adaptation (de Eyto et al, 2007), and several studies indicate that MHC genes, as well as a number of linked loci, can be more powerful than neutral microsatellites in detecting population differentiation in spatially structured fish species such as salmonids (Bernatchez and Landry, 2003;Beacham et al, 2005;Hansen et al, 2007). However, with the exception of a precursory characterization of the MHC class IIA gene and an embedded microsatellite locus in Atlantic herring (Stet et al, 2008), no studies exist to date that describe the MHC variation in an abundant and fully marine fish.…”

Contrasting responses to selection in class I and class IIα major histocompatibility-linked markers in salmon

“…Previous studies in salmonids found temporal stability at MHC class I (Hansen et al, 2007) and class II (Miller et al, 2001) genes and higher levels of population structuring at MHC class II Heath et al, 2006), although guppies seem to show low levels of differentiation on MH class II genes (Van Oosterhout et al, 2006), and evidence from mammals and birds suggests that there is temporal variation in selection acting at MHC class II and class I genes (Westerdahl et al, 2004;Charbonnel and Pemberton, 2005). Our finding of different responses to selection of an MH class IIa-linked marker and a class I-linked marker might reflect an association between level of environmental heterogeneity (within and among rivers) and possibly differences in pathogen-driven selective pressures acting on variability at each class of MH locus (Paterson, 1998;Wegner et al, 2003Wegner et al, , 2008.…”