Introduction
Determining the role of the host genetic architecture in driving variation of fitness-related traits is critical to determining a population's evolutionary trajectory (Carlson & Seamons, 2008). In the past decade, the microbiome, defined as a community of microbes that live in or on a multicellular organism, has emerged as a factor associated with host fitness (Rosshart et al., 2017; Suzuki, 2017; Gould et al., 2018). Particular interest has been given to the microbiome of the gastrointestinal tract (“gut microbiome”), where it plays important roles both in the health and development of the host (reviewed in Nayak, 2010; Romero, Ringø & Merrifield, 2014; Ghanbari, Kneifel & Domig, 2015). In fish, the gut microbiome (hereafter, "microbiome") has been shown to be symbiotically associated with the host, and it plays many beneficial roles, such as aiding in metabolism (Semova et al., 2012; Tremaroli & Bäckhed, 2012), immunity (Galindo-Villegas, García-Moreno, de Oliveira, Meseguer, & Mulero, 2012; Milligan-Myhre et al., 2016), and development (Bates et al., 2006). As such, the microbiome generally reflects host species (Ye, Amberg, Chapman, Gaikowski & Liu, 2014), life stage (Llewellyn et al., 2016), diet (Bolnick et al., 2014a; Bolnick et al., 2014b; Webster, Consuegra, Hitchings & de Leaniz, 2018), physiology (Bolnick et al., 2014b; Ye et al., 2014), geographical isolation (Ye et al., 2014; Webster et al., 2018), and genetic divergence (Sullam et al., 2015; Webster et al., 2018). While the gut microbiome for many fish species has been characterized, the role of host genetics is understudied (Nayak, 2010; Llewellyn, Boutin, Hoseinifar & Derome, 2014; Ghanbari et al., 2015; Sullam et al., 2015), especially with regards to the host genetic architecture acting among and within populations.
The genetic architecture components underpinning microbiome variation are best quantified in humans (Goodrich et al., 2016a), with a limited number of studies in other vertebrate mammals such as mice (Mus musculus, Snijders et al., 2016), pigs (Chen et al., 2018), and red squirrels (Tamiasciurus hudsonicus, Ren et al., 2017). In fish, however, the contribution of the host genetic architecture, including its interaction with the environment, is not well characterized following a quantitative genetics approach, despite a wealth of published fish microbiome studies (Wong & Rawls, 2012; Bolnick et al., 2014b; Ghanbari et al., 2015). With over 32,000 described species (Eschmeyer & Fong, 2015), fish comprise more than half of the known vertebrate species and encompass a wide range of phenotypes, life histories and ecologies (Neslon, Grande & Wilson, 2016). Perhaps among the best studied genetic architectures of non-model animals, and of fish, in general, are those of salmonids’, including the Pacific salmon (Waples, Naish & Primmer, 2019). Here, we focus on the microbiome of Chinook salmon (Oncorhychus tshawytscha), an anadromous and semelparous salmonid recognized as the largest species in its genus (Rounsefell, 1958; Quinn, 2018; Ohlberger, Ward, Schindler & Lewis, 2018). Through aquaculture production of over 14,800 tonnes, the economical contributions of Chinook salmon top 190 million USD across in 2017, with an additional estimated 5,750 capture tonnes (FAO, 2017). Furthermore, Chinook salmon are a key species throughout their range for evolutionary relationships (Waples et al., 2004) and ecologies (Bernatchez & Dodson, 1987; Cederholm, Kunze, Murota & Sibatani, 1999; Koehler et al., 2006). Small sample-size studies have recently accomplished the sequencing of the mid- (n = 30, Ciric et al., 2019) and distal-guts of Chinook salmon (n = 4, Booman et al., 2018; n = 30, Ciric et al., 2018), but no studies have investigated the role of host genetics on its microbiome.
Given that the host controls intestinal mucosa and immune factors that play essential roles in the establishment and maintenance of the microbiome (Spor, Koren & Ley, 2011; Romero et al., 2014; Ghanbari et al., 2015), it is expected that host genome variation may play a role in shaping the microbiome. Indeed, using high throughput sequencing technology, studies have shown the effects of host genetic variation on the microbiome at three levels of host biological organization in fish. First, at the among species level, it known that microbiome variation occurs among taxonomically related species reared in the same or related environments, suggesting a role of host genetics in microbiome community structure (e.g. between silver carp (Hypophthalmichthys molitrix) and gizzard shad (Dorosoma cepedianum), Ye et al., 2014; channel catfish (Ictalurus punctatus), largemouth bass (Micropterus salmoides) and bluegill (Lepomis macrochirus), Larsen, Mohammed & Arias, 2014; grass carp (Ctenopharyngodon idellus), crucian carp (Carassius cuvieri), and bighead carp (Hypophthalmichthys nobilis), Li et. al 2015).
Second, at the among-populations, within-species level, studies have demonstrate the effects of genetic divergence among populations reared in either wild or artificial environments on the microbiome in Trinidadian guppies (Poecilia reticulata, Sullam et al., 2015) Atlantic salmon (Salmo salar;  Webster et al., 2018) and zebrafish (Danio rerio, Roeselers et al., 2011). Although those studies did not account for environmental variation by using common environments, they nonetheless showed strong population effects on the microbiome, with some attributing the observed interpopulation effects on microbiome variation to environmental variation (Roselers et al., 2011; Webster et al., 2018). Given that variation in the environment contributes strongly to microbiome variation (e.g. due to diet, Naverrete et al., 2012; Wong et al., 2013; or rearing environments, Webster et al., 2018 and Parshukov et al., 2019), this is not a surprising outcome. However, it does underscored the need to control for rearing environment in explicitly determining host genetic architecture component effects (Goodrich et al., 2014a; Ghanbari et al., 2015). However, among-population effects on microbiomes have been used to deduce putative microbial roles in host adaptation (Sullam et al., 2015; Webster et al., 2018). Both neutral (Roeselers et al., 2011; Sullam et al., 2015) and selection based (Sullam et al., 2015; Webster et al., 2018) evolutionary processes have been invoked in explaining divergent microbiomes across populations; however, evidence for both is inconclusive.
Third, at the within-population, within species level, studies have shown the effects of host-related factors on microbiome diversity and function (e.g. Bolnick et al., 2014b); however, there are no studies demonstrating the role of genetic architecture, especially using related families within a population to partition host genetic variance components. Despite this, we can indirectly infer from 16S rRNA-based studies that within-population effects contribute less strongly than among population-level effects in Atlantic salmon (Webster et al., 2018), and diet in rainbow trout (Oncorhynchus mykiss, Navarrete et al., 2012). Addressing the knowledge gap regarding within-population host genetic architecture effects would allow the estimatation of heritable components in the microbiome, defined as the proportion of phenotypic variance in a population attributable to additive genetic variance (Visscher, Hill & Wray, 2008). Collectively, the literature shows that the host genome plays a pivotal role in determining the composition of the microbiome across various fish species, but there is still a gap in our knowledge regarding the effects of various host genetic architecture components on their microbiomes. It is shown then, overall, that measuring the extent of gut microbiome variation among and within populations is important in efforts pertaining to the management and conservation of salmonids (Garcia de Leaniz et al., 2007).
This study aims to address two main questions: 1) do evolutionary forces reflective of genetic divergence among natural populations affect the microbiome composition in controlled hybrid crosses of Chinook salmon?, and 2) are there within-population sire effects that act on the microbiome differentially among populations, reflective of additive genetic variance effects? Salmonids are known to lend themselves to traditional breeding designs, permitting us to partition genetic and environmental sources of variance (Lynch & Wash, 1998). Here, we reared half-sib families from a single fully-domesticated and seven wild-domestic hybrid crosses of Chinook salmon in replicated pens to test for population and within-population additive genetic effects on gut microbiome diversity and composition.