The Genetic Architecture of Domestication in Animals

Chickens

The comb of the chicken has been a source of interest since the early days of genetics, when Bateson and Punnett used the pea comb, rose comb, and walnut comb mutations to illustrate the first example of Mendelian inheritance and epistasis in animals.²⁵ These comb mutations were all identified in domesticated chickens and have subsequently been identified at the genomic level.^26,27 Given that these were used as a model of Mendelian inheritance, it is hardly surprising that they are monogenic in effect (although the rose comb and pea comb mutations do interact epistatically to reveal a further comb phenotype – the walnut comb). Other monogenic domestication traits have also been identified in the chicken – principally yellow skin color (controlled by the BCDO2 gene),²⁸ duplex comb,²⁹ and barred coat color genes.³⁰

Dogs

In dogs, strong breed differences and extreme inbreeding have aided in the identification of numerous monogenic genes affecting the domesticated phenotype. Genes for wrinkled skin,³¹ leg length,³² and body size³³ have all been discovered. In the case of the last two genes, these traits are also quantitative, though the genes identified explain virtually all the variations between long- and short-legged breeds of dogs, and large and small breeds. Almost all fur growth type and texture phenotypes have also been shown to be explained by only three genes (FGF5, KRT71, and RSPO2).³⁴

Cattle, sheep, and horses

In cattle, a deletion mutation has been identified in the MSTN gene that leads to extreme muscular development (an increase in muscle mass of 20%),³⁵ with the same gene that causes this increased musculature also exhibiting similar effects in sheep.³⁶ Regarding production traits in cattle, a nonsense mutation in the gene FMO3 has been identified as causing a characteristic fish-odor in milk from cattle.³⁷ Also relating to milk production, the DGAT1 gene accounts for 30% of the variation in fat percentage in milk,³⁸ while the ABCG2 gene affects milk composition.³⁹ Other domestication-related genes have also been identified in the sheep. The gene RXFP2 has been linked with horn type,⁴⁰ though in this case no functional data or mutation identification is currently available to confirm this effect. Also in sheep, an X-linked mutation in a specific breed causes increased ovulation rate and twin births,⁴¹ while an autosomal mutation in BMPR1B causes the Booroola phenotype that also affects ovulation.⁴² In horses, the gene DMRT3 has recently been shown to be required for the unique gait types present in Icelandic horses.⁴³ In the case of the DMRT3 locus, this is particularly intriguing as it is probably the only major gene identified in domestic animals that can be thought of as modifying behavior.

Pigs

In pigs, a major gene for malignant hyperthermia has been associated with the ryr1 gene⁴⁴ that also controls meat quality traits, while a nonconservative mutation in the gene PRKAG3 leads to high glycogen content in muscles.⁴⁵ A gene affecting muscularity has also been identified in pigs (IGF2), which also affects back fat and heart size,⁴⁶ while the gene PPARD has been identified as affecting ear size.⁴⁷ In both the latter cases, the traits are fully quantitative, yet the identified genes account for a large percentage of the trait variation – 40% in the case of PPARD and 15%–30% in the case of IGF2. Polymorphisms in the CAST gene have also been associated with meat tenderness in pigs, though more in-depth functional assays have yet to be made beyond this association.⁴⁸

Quantitative trait loci studies

In the examples shown earlier, the bulk of major genes identified act in a monogenic fashion, in that they explain almost all the variation of the traits they regulate. A few of the genes in question are part of the architecture of a standard quantitative trait, though certainly examples are present (as discussed earlier). In terms of analyzing whether major genes are more prevalent in domesticated species, it is important to bear in mind that the identification of the actual causal genes or mutation is extremely rare. In contrast, more standard Quantitative Trait Loci (QTL) mapping studies can be used to identify the overall genetic architecture of a trait in terms of estimating the number of loci involved and their relative strength of effect.⁴⁹ Such studies are far more abundant and still give an idea of the underlying architecture. There are, of course, problems with this approach. The use of an F₂ or similar type of second-generation intercross population means that the resolution in terms of the size of the QTL regions identified is far too low for candidate gene identification. Each QTL typically covers a span of ~20–30 cM, depending on the size of the cross, which can equate to hundreds or thousands of genes, depending on the genome size and recombination rate of the species used. This low resolution, caused by the limited number of recombinations that have accrued in these intercross populations, can also lead to a misleadingly simplified genetic architecture. This potential problem occurs when a QTL is in fact made up of multiple smaller loci; however because of the low number of recombinations present in the population and hence the poor resolution, these manifest as a larger effect and would be falsely described as a major gene/QTL effect. Similarly, if the loci are antagonistic (ie, have the opposite direction of effect in terms of the additive effect of each sublocus), a QTL may be missed. Nevertheless, the relative ease of performing a QTL analysis means the number of identified loci and the number of successful studies are very high, allowing a more holistic examination of the prevalence of major genes (or rather major-effect QTL). Table 2 lists the current genome build and online QTL resources for the domestic animals listed below.

In the chicken, major-effect loci have been identified for comb mass,⁵⁰ growth,^13,51 and susceptibility to feather pecking.⁵² In contrast, most other traits measured in domestic chickens compared to their wild counterparts show more standard effect sizes (mean ~5%)^49,53 and no large-effect genes have been found in traits ranging from bone allocation,^54,55 fear-avoidance behavior,^12,56 onset of sexual maturity,¹⁵ number of eggs produced,⁵⁷ and production characteristics (muscle pH, color, and egg taste).⁵⁸

In pigs, QTL for a wide variety of production-related traits have been identified, including teat number,⁵⁹ porcine leukocyte count,⁶⁰ carcass quality and growth traits,^61–63 meat quality⁶⁴ and pH,⁶⁴ litter size/fecundity,⁶⁵ and disease resistance.⁶⁶ There are well over 100 QTL studies involving the pig, with the results summarized in several reviews^65–67 and a pig QTL database.⁶⁸ Some large-effect QTL have been observed, including loci for shoulder weight, loin weight and ham weight,⁶³ and pH,⁶⁴ with the rest being standard effect sizes.

A multitude of QTL studies in cattle have looked at characteristics such as growth, meat quality, milk composition, behaviour, fecundity and reproduction, mastitis and pigmentation. For a full summary, the bovine QTL website (http://bovinegenome.org/bovineqtl_v2/login.jsp) gives a full list of location, effect, and breed, among other information. Of the QTL, once again the majority are of standard (ie, relatively modest) effect sizes, though milk composition and pigmentation traits contained major loci (with the genes identified, as discussed earlier).

Summary of major genes in domestication

A common pattern occurs in almost all the domestic species – although some major genes are present, this does not appear to be the norm for the bulk of the loci that affect these domestication characters. The fact that such loci are present at all is most likely because of the strong directional selection brought about by domestication, as it would be relatively easy to identify and fix such polymorphisms/mutations as they are phenotypically identified. Further evidence for this directional selection favoring some major gene effects is also provided by the genetic architecture of morphology in the dog. The dog has undergone some of the most extreme directional selection among domesticated animals, leading to the most phenotypically diverse mammalian species on the planet.⁶⁹ This selection, in combination with the extreme inbreeding within breeds, appears to have led to a remarkably simple genetic architecture, especially for morphological traits. Numerous monogenic mutations have therefore arisen in the dog and aided gene identification, while even more standard morphological studies tend to have >70% of the variation explained by two to six QTL.⁷⁰ Reasons posited for this simplistic architecture have been based on the fact that many modern breeds were created during the Victorian era, when breeders focused heavily on novelty and the preservation of discrete mutations.⁷⁰ Such discrete mutations would then be easy to breed into a variety of different genetic backgrounds, which then expanded the breed diversity. This is potentially at odds with the selection occurring in other domesticated breeds, where selection instead is being directed on economically important traits by using the standing genetic variation already present within a wild population, rather than large-effect discrete mutations. This would then imply that the large-effect genes that have been identified across domesticated species are more recent mutations that were far easier to select on, whereas the bulk of the variation present in a domestic species came from the standing variation present in the wild progenitors.

Evidence for pleiotropy in domestication

Perhaps the best evidence for pleiotropy is the correlations that exist between separate components of the domestication syndrome when domestication is recreated through selection lines. The most well known of these selection lines was based on the silver fox and consisted of directional selection solely based on tameness and aggression.^72,80 It was found that after only 8–10 generations, color changes appeared (yellowing and piebaldness), adults maintained the juvenile floppy ears, skull changes occurred (leading to short and wide faces), as did curly tails.^79,81 These results suggest that selection on a single behavioral trait can lead to a range of morphological changes. In a similar experiment, rats also divergently selected for tameness/aggression exhibited changes in neurotransmitters, hormone levels, and morphology.^82,83 These studies imply that the loci for tameness show pleiotropic effects on multiple different domestication syndrome traits, though in these instances close linkage between different genes affecting each trait could also be a potentially plausible explanation.

If pleiotropy is occurring, QTL studies between wild and domestic animals should show an overlap between the multiple different domestication traits. Plant and animal studies using this mapping approach show a marked similarity in their findings. Multiple domestication traits are found clustered fairly closely together throughout the genome. These clusters are fairly loose, typically ≥20–30 cM (1 cM roughly equates to a 1% recombination rate, with the physical distance varying depending on the species in question – in human beings and mice, in a standard design, 1 cM is ~1 Mb; in chickens, 1 cM is ~350 kb). In plants, these clusters have been found in beans,^84,85 maize,^86,87 sunflowers,⁸⁸ rice,⁸⁹ and pearl millet.⁹⁰ Initial work using the aforementioned rat selection lines found that when divergent lines were crossed together to map the underlying genes, clusters of QTL were also once again revealed. In the case of the rat, these were in two clusters spanning 41 and 29 cM, respectively.⁸² Using an intercross between wild and domestic chickens, QTL clusters were found that indicated multiple different trait types were overlapping,¹³ with loci for comb size (a sexually selected ornament in the chicken) overlapping with onset of sexual maturity loci,¹⁵ as well as with bone density and egg production traits.⁵⁷ In the silver foxes differentially selected for behavior (also mentioned previously), a QTL analysis for behavior indicated an overlap between different behavioral QTL, though this study was restricted to behavioral traits, so other characteristics were not mapped simultaneously.⁹¹

The problem with these examples is related to the mechanics of QTL analysis as it is generally performed. All these studies use variations on an F₂ intercross, meaning that the resolution of such studies tends to be rather low, with the confidence intervals (~30 cM or more) equating to at least this number of megabases in almost all the species examined. Loci can be overlapping but this may be because of linkage (ie, close physical proximity between loci) rather than direct pleiotropy from a single causal loci. For example, in the case of the wild x domestic chicken study, statistical analysis aimed at separating these two states found that most clusters in the F₂ population appeared to be due to linkage, with only the central core of QTL in each cluster unable to be distinguished as either closely linked or pleiotropic.¹³ To ascertain if true pleiotropy is occurring in such clusters, there are a number of techniques that can be used. First, you can attempt to increase the number of recombinations to expand the genetic map, by intercrossing for further generations (thereby increasing the resolution of the detected QTL).⁹² If these loci are pleiotropic, then the clusters should remain the same size, rather than expanding along with the map. In the case of the chicken intercross, this was expanded to eight generations of intercrossing, with the result being far narrower intervals generated. One such locus affecting comb size was reduced to 600 kb, with only two genes in the interval, and with expression analyses indicating greater effects from one gene, HAO1.⁵⁰ This gene was also found to show pleiotropic effects on bone and egg production characteristics, once again using a combination of QTL analysis and gene expression correlations between the traits and genes involved. When a more global expression QTL (eQTL) analysis of both comb and bone samples was performed (enabling multiple genes to be tested for effects on expression in both comb and bone tissue), results suggested that both pleiotropy and linkage were present.⁹³

To truly define pleiotropy, however, the actual causal mutation/polymorphism must be identified. In this instance, it is possible to identify genuine pleiotropic effects. Unfortunately, as shown earlier, the identification of such loci is extremely rare. More plant-based examples exist than their animal counterparts, and even here, the polymorphisms that are more readily identified are most commonly of very large effect. This makes them almost functionally identical to major genes rather than the small-effect loci more commonly associated with quantitative traits. Although this review focuses on animal domestication, plant genetics has some surprising and relevant results to elucidate the mechanisms at work. Where polymorphisms have been identified, there appears to be pleiotropy. The Q locus in wheat affects a variety of traits, including free-threshing and floral development characteristics,^94,95 and the tb1 locus in maize affects a variety of domestication characters.^87,96 However, in the case of tb1, there are also other mutations in linked loci that affect domestication traits.^86,87 Other examples demonstrate that, in fact, different mutations can be present in close proximity. The shattering mutation in rice is a single recessive mutation that is tightly linked to loci affecting seed dormancy and the pericarp.⁹⁷ Animal examples of the identification of the causal mutation for a quantitative trait in a domestic animal includes the IGF2 mutation in pigs, which also affects muscle mass and fat deposition.⁴⁶ Somewhat strikingly, many of the other mutations identified in animals do not exhibit extensive pleiotropy, and certainly none of the extreme pleiotropy that would be required to explain some of the more diverse aspects of the domestication syndrome. Therefore, it seems that if one considers both plant and animals examples, pleiotropy does exist, and also that domestication mutations often exist in linked groups of multiple mutations/genes (certainly in the case of plant domestication genetic architecture).

It is also of interest to compare the extent of pleiotropy as seen in domestication with that observed in quantitative traits in general. One issue here is that there are several different types of quantitative traits (morphological, behavioral, and life history in general) that may be under very different forms of selection. The extent of pleiotropy present in general was thought to be high because of predictions based on extensions of Fisher’s geometric model. This led to the universal pleiotropy hypothesis that states that pleiotropy arises so frequently as to almost be considered universal.⁹⁸ Pleiotropy is also the foundation of the cost of complexity hypothesis, which posits that complex organisms are less adaptable or responsive to evolution because of the increased degree of pleiotropy that is present.^99,100 However, despite these hypotheses,⁹⁸ QTL studies in general have found there to be less pleiotropy than expected (see pleiotropic scans in mice¹⁰¹ and stickleback¹⁰²). Similarly, empirical data from gene knockout and knockdown experiments in a variety of taxa ranging from yeast to mice also indicates that pleiotropy is generally fairly low (see the review by Wagner and Zhang¹⁰³). It therefore appears that domestication traits do not appear to exhibit more pleiotropy than quantitative traits in general, though with the caveat that additional mutation identification is most likely required to verify this statement.

Phenotypic buffering, eQTL, and pleiotropy

Phenotypic buffering was first proposed by Waddington and was initially used to explain how the phenotype of an animal could be resilient to genetic and environmental perturbations.¹⁰⁴ This idea has recently been taken into account for potential pleiotropy in eQTL analyses – if buffering is correct, then when certain key loci are perturbed, this will lead to a raft of other changes being revealed. The underlying mutations would no longer be buffered, hence their effects would then be revealed by the single buffering locus alteration. eQTL analysis itself consists of standard QTL mapping, though in this instance uses global gene expression from a particular tissue as the source of the phenotypes. By combining these with the genotypic information of each individual, it is possible to map genes that vary according to their underlying genotype. This should then be observed by hotspots in the eQTL with multiple trans effects, showing genes from dispersed areas of the genome are all controlled by a single genetic locus.^105,106 Although the resolution issues of QTL analysis can once again be an issue here, the phenotype (gene expression) tends to be less noisy than conventional analysis. Where such analysis has been performed, pleiotropic hotspots appear to be rather limited, even when they are found. For example, in the study by Fu et al,¹⁰⁶ several phenotypic hotspots were found, as were hotspots for metabolite abundance; yet, these were only reflected in a single eQTL hotspot. Chesler et al found a relatively small number of QTL correlated with large gene expression modules situated in the genome, hypothesizing that this indicated pleiotropy.¹⁰⁷ If multitrait pleiotropy for the domestication syndrome does exist, then obviously such eQTL hotspots should also be observed in wild × domestic intercross eQTL analyses. In the case of the rat lines divergently selected for tameness, an eQTL analysis was performed on 150 individuals and only identified one locus that contained more trans eQTL than was expected by chance, with this being only just significant (seven in the region and six expected by chance),¹⁰⁸ with this hotspot not overlapping any of the tameness QTL. In the case of the chicken, multiple tissues have been used for this type of eQTL analysis. In bone samples, some trans hotspots occurred, though most did not overlap any of the bone QTL observed.⁵⁵ Therefore, a similar pattern is once again seen as with major gene pleiotropy.