Using genome-wide measures of coancestry to maintain diversity and fitness in endangered and domestic pig populations

Conservation and breeding programs aim at maintaining the most diversity, thereby avoiding deleterious effects of inbreeding while maintaining enough variation from which traits of interest can be selected. Theoretically, the most diversity is maintained using optimal contributions based on many markers to calculate coancestries, but this can decrease fitness by maintaining linked deleterious variants. The heterogeneous patterns of coancestry displayed in pigs make them an excellent model to test these predictions. We propose methods to measure coancestry and fitness from resequencing data and use them in population management. We analyzed the resequencing data of Sus cebifrons, a highly endangered porcine species from the Philippines, and genotype data from the Pietrain domestic breed. By analyzing the demographic history of Sus cebifrons, we inferred two past bottlenecks that resulted in some inbreeding load. In Pietrain, we analyzed signatures of selection possibly associated with commercial traits. We also simulated the management of each population to assess the performance of different optimal contribution methods to maintain diversity, fitness, and selection signatures. Maximum genetic diversity was maintained using marker-by-marker coancestry, and least using genealogical coancestry. Using a measure of coancestry based on shared segments of the genome achieved the best results in terms of diversity and fitness. However, this segment-based management eliminated signatures of selection. We demonstrate that maintaining both diversity and fitness depends on the genomic distribution of deleterious variants, which is shaped by demographic and selection histories. Our findings show the importance of genomic and next-generation sequencing information in the optimal design of breeding or conservation programs.The main goal in population management is to maintain the most genetic diversity to maximize the survival potential of the population, as well as to potentially select variants that have fitness consequences (Frankham et al. 2002). Conservation programs usually use small numbers of breeding individuals, and thus, genetic variation can decrease rapidly. In commercial breeding programs, artificial selection can lead to a reduction in overall diversity and an increase in inbreeding (Lush 1946). This can have highly detrimental consequences if breeds lose their ability to adapt to different environmental conditions or if deleterious variants are linked to selected loci. Conservation and commercial breeding programs, therefore, are not so different in their approach of managing their populations, although their ultimate goals differ. Inbreeding depression (Charlesworth and Charlesworth 1987) is a common phenomenon in captive populations of many wild species like wolves (Laikre and Ryman 1991) and also in many breeds of domesticated species like dogs (Leroy 2011; O''Neill et al. 2014). Thus, breeders are aware of the need to maintain diversity while also preserving genetic variants that confer desired, distinct phenotypes.For this purpose, controlling the inbreeding rate and, therefore, optimizing the effective population size, is required. Currently, the best known method to achieve these goals is optimal contributions (OC). This method determines the number of offspring that each individual of the current population should contribute to the next generation so as to minimize global coancestry (Ballou and Lacy 1995; Meuwissen 1997; Grundy et al. 1998). Relatedness, i.e., coancestries between individuals, is needed to apply OC in any management program. Traditionally, genealogical coancestries were used when OC were first proposed because marker data were scarce (Ballou and Lacy 1995). Currently, OC based on molecular coancestry is the best way to maintain the most diversity in terms of heterozygosity, provided genotypes are of high density (de Cara et al. 2011; Gómez-Romano et al. 2013). However, management of populations using OC with molecular coancestry may lead to a fitness decrease, since deleterious alleles linked to the markers used to measure coancestry will be maintained (de Cara et al. 2013a). Recently, a measure of coancestry based on shared genomic regions has been proposed as a compromise to maintain both fitness and genetic diversity when the population in the program has a medium to high inbreeding load (de Cara et al. 2013b). One of the aims of this approach is to avoid the occurrence of long runs of homozygosity (ROH) in the offspring, which are characteristic of reduced diversity, due either to selection or bottlenecks and therefore, may confer inbreeding depression (Keller and Waller 2002; Szpiech et al. 2013; Curik et al. 2014). Determining the occurrence of segments of identity by descent (IBD) in potential parents, thereby measuring their relatedness and coancestry, can be used to minimize the occurrence of ROHs in the offspring.Predictions for management based on genealogical, molecular, or IBD segments have been made with simulated data (de Cara et al. 2013b), but have so far not been tested with actual genotype data. Pigs are an excellent model for testing the use of genetic data in population management. Various molecular data sources are available, like a high-quality genome reference (Groenen et al. 2012) and genotyping arrays (Ramos et al. 2009). Pedigree information is also available for a variety of breeds and other captive populations. Pigs display a high degree of heterogeneity in the occurrence of ROHs (Bosse et al. 2012), which to a large extent reflects differences in their demographic histories. The domesticated pig Sus scrofa consists of many commercial breeds that are under strong artificial selection for commercial traits. Although this particular species is widespread in captivity as well as in the wild, other pig species within the genus Sus only occur on a few islands in Southeast Asia and are critically endangered, like the Visayan warty pig Sus cebifrons (Larson et al. 2005, 2007; Groves 2008). Breeding programs for S. cebifrons in zoos have been set up to maintain the species at least in captivity.Here, we combine pedigree information, genotype data, and next-generation sequencing data to perform in silico management of two pig populations with distinctly different histories: a commercially maintained population of the Pietrain breed of S. scrofa; and a captive zoo population of the critically endangered S. cebifrons species. By comparing the decay of heterozygosity over 10 generations, we assess which of three management strategies maintains the most diversity. These strategies are based on (1) genealogical coancestry; (2) molecular marker-by-marker coancestry; or (3) shared regions of the genome. As S. cebifrons is known to have undergone recent bottlenecks that have led to establishing the conservation programs for this species in captivity, we infer the demography of Sus cebifrons to determine the effect of population-specific demography on the management outcome. On the other hand, to understand the effect of the management strategy on ongoing selection in the population, we identify signatures of selection in the Pietrain breed before and after management. Thus, we investigate whether the best strategy is sensitive to demographic history or initial patterns of variation in the population and how this information is relevant to conservation practitioners; and by analyzing signatures of selection, we address whether any of the management strategies may interfere with selection goals by erasing these signatures. Finally, by predicting fitness based on deleterious variants in the genome in both populations, we show the performance of each of these management strategies not only on diversity but also on fitness because ignoring the latter could lead to the accumulation of deleterious variants, loss of viability, and potentially to extinction of the population in a conservation program.