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Runs of homozygosity - degree of inbreeding and disease associations

Runs of homozygosity - degree of inbreeding and disease associations

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Been reading recently about methods to determine how inbred a particular person is by measuring their "runs of homozygosity." Loosly, these are defined as regions of the genome (typically >1Mb) where the person is homozygous for all polymorphisms, suggesting their parents were identical for this region. If a person has 'many' of these regions, it suggests their parents were closely related.

A study in 2015 [1] found some evidence that people with more regions of homozygosity had higher risk of heart disease.

My question firstly relates to the amount of homozygosity you might expect in a 'normal' out-bred person, compared to an in-bred population (e.g. small community), and then to 'extreme' examples of relatedness (parent/child offspring). In my searching I didn't see any cut-offs, if they exist, or whether this is even the right way to be thinking about it. And secondly, just how bad is it to have these runs?

  1. Christofidou P, et al. Runs of Homozygosity: Association with Coronary Artery Disease and Gene Expression in Monocytes and Macrophages. Am J Hum Genet. 2015; 97:228-237. PMID: 26166477.

The Relationship between Runs of Homozygosity and Inbreeding in Jersey Cattle under Selection

Affiliations Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America, Department of Animal Science, Iowa State University, Ames, Iowa, United States of America

Affiliation Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America

Affiliation Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America

Affiliation Animal Genomics & Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, United States of America

Affiliation Department of Animal Science, Iowa State University, Ames, Iowa, United States of America

Runs of homozygosity and inbreeding in thyroid cancer

Background: Genome-wide association studies (GWASs) have identified several single-nucleotide polymorphisms (SNPs) influencing the risk of thyroid cancer (TC). Most cancer predisposition genes identified through GWASs function in a co-dominant manner, and studies have not found evidence for recessively functioning disease loci in TC. Our study examines whether homozygosity is associated with an increased risk of TC and searches for novel recessively acting disease loci.

Methods: Data from a previously conducted GWAS were used for the estimation of the proportion of phenotypic variance explained by all common SNPs, the detection of runs of homozygosity (ROH) and the determination of inbreeding to unravel their influence on TC.

Results: Inbreeding coefficients were significantly higher among cases than controls. Association on a SNP-by-SNP basis was controlled by using the false discovery rate at a level of q* < 0.05, with 34 SNPs representing true differences in homozygosity between cases and controls. The average size, the number and total length of ROHs per person were significantly higher in cases than in controls. A total of 16 recurrent ROHs of rather short length were identified although their association with TC risk was not significant at a genome-wide level. Several recurrent ROHs harbor genes associated with risk of TC. All of the ROHs showed significant evidence for natural selection (iHS, Fst, Fay and Wu's H).

Conclusions: Our results support the existence of recessive alleles in TC susceptibility. Although regions of homozygosity were rather small, it might be possible that variants within these ROHs affect TC risk and may function in a recessive manner.

Keywords: GWAS Inbreeding Runs of homozygosity Thyroid cancer.

Fine-Scale Resolution of Runs of Homozygosity Reveal Patterns of Inbreeding and Substantial Overlap with Recessive Disease Genotypes in Domestic Dogs

Inbreeding leaves distinct genomic traces, most notably long genomic tracts that are identical by descent and completely homozygous. These runs of homozygosity (ROH) can contribute to inbreeding depression if they contain deleterious variants that are fully or partially recessive. Several lines of evidence have been used to show that long (> 5 megabase) ROH are disproportionately likely to harbor deleterious variation, but the extent to which long vs. short tracts contribute to autozygosity at loci known to be deleterious and recessive has not been studied. In domestic dogs, nearly 200 mutations are known to cause recessive diseases, most of which can be efficiently assayed using SNP arrays. By examining genome-wide data from over 200,000 markers, including 150 recessive disease variants, we built high-resolution ROH density maps for nearly 2,500 dogs, recording ROH down to 500 kilobases. We observed over 678 homozygous deleterious recessive genotypes in the panel across 29 loci, 90% of which overlapped with ROH inferred by GERMLINE. Although most of these genotypes were contained in ROH over 5 Mb in length, 14% were contained in short (0.5 - 2.5 megabase) tracts, a significant enrichment compared to the genetic background, suggesting that even short tracts are useful for computing inbreeding metrics like the coefficient of inbreeding estimated from ROH (FROH). In our dataset, FROH differed significantly both within and among dog breeds. All breeds harbored some regions of reduced genetic diversity due to drift or selective sweeps, but the degree of inbreeding and the proportion of inbreeding caused by short vs. long tracts differed between breeds, reflecting their different population histories. Although only available for a few species, large genome-wide datasets including recessive disease variants hold particular promise not only for disentangling the genetic architecture of inbreeding depression, but also evaluating and improving upon current approaches for detecting ROH.


In common with recent studies of European-heritage populations [1], [4], [6], our analysis of this globally representative sample confirms that runs of homozygosity longer than 0.5 Mb are ubiquitous and frequent across all populations. Comparison of the number and sum length of ROH of various sizes to the mean inbreeding coefficient and effective population size indicate that ROH provide a valuable record of a population's demographic history. Moreover, ROH record the demographic history of the ancestors of the individual. In fact, in most populations individual ROH profiles cluster, particularly in terms of the number of ROH. Four classes of population can be distinguished on the basis of the length and number of ROH, which describe a demographic historical space. First the consanguineous populations from South and West Asia stand out in carrying significantly more very long ROH than the African and other Eurasian populations. Second the Oceanian populations are unique in having very large numbers of shorter ROH, but few long ROH, consistent with a reduced Ne in the past, but little inbreeding in recent times. Third the Native American populations have more short and long runs than any other population, indicating both ancient and recent parental relatedness. Fourth, the Europeans, East Asians and Africans show only the background level of shared ancestry relating to their continental Ne.

The distribution of the shorter (0.5–2 Mb) ROH across the globe mirrors other aspects of human variation in reflecting our origin in sub-Saharan Africa and subsequent dispersals out of Africa, finally reaching Oceania and America. Analysis of ROH in three populations using 3.1 million markers revealed the same Africa, Europe, East Asia ranking [5]. The shortest category of ROH considered here (0.5–1 Mb) were inversely correlated with estimates of male Ne based on Y chromosome diversity. We note that the Y chromosome estimates of Ne are derived from independent data and thus avoid the circularity of comparing homozygosity with estimates of Ne derived from LD, which itself influences ROH. It must be remembered that the Y chromosome only records male history and furthermore represents only one realisation of the evolutionary process, so it will be interesting to compare to estimates of effective population size which also include mtDNA and/or whole genome variation. Longer ROH provide information on more recent ancestry, from population size and endogamy to recent inbreeding. However, unlike genetic diversity, linkage disequilibrium and other summary statistics of gene genealogies, ROH are an individual-level phenomenon and so provide a distinctive record of the demographic history of an individual's ancestors.

The increased numbers and so total length of ROH from 0.5–2 Mb in certain populations is likely to be the result of common extended haplotypes reaching high frequencies in these small, isolated communities, such that they are frequently inherited from both parents. Such patterns of haplotype sharing – among individuals or among parents of individuals – can also be described as correlations among alleles at different loci or LD. Because we are interested in the potential expression of recessive effects, we include ROH regardless of local patterns of LD the small sample sizes available also prevent unbiased estimates of LD. These shorter ROH do not arise from inbreeding in recent generations and are common in all of the populations represented in the HGDP. In all populations shorter ROH make up the bulk of the homozygosity present. Even in the most inbred populations, the total length of the genome in shorter ROH (0. 5–2 Mb) is more than that in longer ROH (over 2 Mb). This point can be illustrated more dramatically by using a panel of 3 million SNPs, which enables the reliable detection of ROH as short as 100 kb. Using this panel, the total ROH length among Han Chinese is ∼510 Mb [5], compared with ∼130 Mb using a panel of ∼400,000 SNPs). Given that shorter ROH account for more of the total homozygosity even in the most inbred people, any effect of ROH on disease risk could also be mediated by these shorter runs, and not only by the long ROH arising from recent parental relatedness.

While there is a distribution of ROH number and length in all populations, this is very variable in consanguineous populations such as the South Asian Baluchi – not everyone has consanguineous parents – and as inheritance is a stochastic process, the outcome can vary widely even between siblings. South Asians living in Europe also show an increased variance in total ROH length [14]. Cryptically inbred outliers can be observed even in large predominantly urban populations, such as the French, Japanese and Mandenka. Such individuals plot to the right of their population in a graph of the number vs. sum length of ROH (e.g. Fig 3), as the relatively small number of very long ROH originating from their recent shared ancestry influence the sum of ROH more than the total number.

The comparison of the number and sum length of runs (e.g. Fig 3) is therefore a useful representation of the demographic history of an individual's ancestors. Individuals falling near the diagonal line carry a complement of ROH deriving from their continental Ne, with the number of ROH being driven mostly by the more numerous shorter runs, which reflect more ancient demographic history. Africans have the lowest number of ROH, followed by South and West Asians, Europeans, East Asians, Oceanians and finally Native Americans. The distance along the sum of ROH axis from the diagonal differentiates individuals primarily in terms of their complement of long runs, and therefore recent inbreeding, with many south and west Asians and Native Americans undergoing a right shift (Fig 3 and File S1).

Individuals from particular populations stand somewhat apart from others of their continent due to a “right shift” (File S1), e.g. most of the very isolated Yakuts, and to a lesser degree some Sardinians, whilst the Maya have less homozygosity than the other Native Americans sampled, perhaps due to European admixture [9].

ROH, like other aspects of our genetic variation including genetic diversity and linkage disequilibrium, demonstrate a strong correlation with distance from East Africa. This pattern was driven mainly by the shorter ROH, consistent with their origin long enough ago to be influenced by serial founder events as humans spread across the globe. Longer ROH were less correlated with walking distance from Africa. When the analyses were repeated without Native Americans, to exclude the possibility of an increase in their homozygosity levels for reasons other than their distance from Africa, the shorter ROH remained highly correlated, but there was no significant relationship between distance from Africa and sum of ROH over 16 Mb in length. The lack of relationship for longer ROH is not surprising, given their very recent origins. The correlation with Out-of-Africa distances for shorter ROH show that patterns of identity-by-descent are structured by our migrations from Africa, not just identity-by-state observed through single SNP analyses of diversity.

Regions of extended homozygosity in the genome can also be a consequence of deletions along the genome. In this study it was not possible to check whether the observed ROH are the result of hemizygous deletions due to the fact that only the called genotyping data were available. However, based on previous studies, it would be reasonable to assume that ROH in this study are true homozygous tracts and not hemizygous deletions – apart from anything else many of the tracts observed here are much larger than typical copy number polymorphisms. Recent studies with access to fluorescent intensity data [1], [15], [16] reported that the observed extended regions of homozygosity are not the result of large deletion polymorphisms. This indicates that long homozygous regions are the result of a single ancestral haplotype being inherited from both parents, rather than the mark of copy number variation.

It is clear that a greater proportion of the genome in ROH will increase the individual risk of recessive Mendelian disease, but if many recessive factors are also involved in complex disease susceptibility, ROH may also confer risk for common diseases such as diabetes and heart disease. In line with this hypothesis, pedigree studies of hypertension and LDL cholesterol [17], quantitative genetic estimates of dominance variance for blood pressure, LDL, fasting insulin and measures of lung function [18] and analysis of genome-wide heterozygosity using microsatellites [19] all suggest that numerous recessive variants contribute to complex disease risk.

Long ROH are a neglected feature of our genome, which we have shown here to be universally common in human populations and to correlate well with demographic history. ROH are, however, only partially predictable from an individual's background (due to the stochastic nature of inheritance). As well as conferring susceptibility to recessive Mendelian diseases, ROH are also potentially an underappreciated risk factor for common complex diseases, given the evidence for a recessive component in many complex disease traits [18] they will allow quantification of the risk arising from recessive genetic variants in different populations.

Fine-scale resolution and analysis of runs of homozygosity in domestic dogs

Inbreeding and consanguinity leave distinct genomic traces, most notably long genomic tracts that are identical by descent and completely homozygous. These runs of homozygosity (ROH) can contribute to inbreeding depression if they contain deleterious variants that are fully or partially recessive. Several lines of evidence have been used to show that long (> 5 megabase (Mb)) ROH are disproportionately likely to harbor deleterious variation, but the extent to which long versus short tracts contribute to autozygosity at loci known to be deleterious and recessive has not been studied.

In domestic dogs, nearly 200 mutations are known to cause recessive diseases, most of which can be efficiently assayed using SNP arrays. By examining genome-wide data from over 200,000 markers, including 150 recessive disease variants, we built high-resolution ROH density maps for nearly 2,500 dogs, recording ROH down to 500 kilobases. We observed over 500 homozygous deleterious recessive genotypes in the panel, 90% of which overlapped with ROH inferred by GERMLINE. Although most of these genotypes were contained in ROH over 5 Mb in length, 14% were contained in short (0.5 - 2.5 Mb) tracts, a significant enrichment compared to the genetic background, suggesting that even short tracts are useful for computing inbreeding metrics like the coefficient of inbreeding estimated from ROH (FROH).

In our dataset, FROH differed significantly both within and among dog breeds. All breeds harbored some regions of reduced genetic diversity due to drift or selective sweeps, but the degree of inbreeding and the proportion of inbreeding caused by short versus long tracts differed between breeds, reflecting their different population histories. Although only available for a few species, large genome-wide datasets including recessive disease variants hold particular promise not only for disentangling the genetic architecture of inbreeding depression, but also evaluating and improving upon current approaches for detecting ROH.


Offspring of biologically related persons are subject to the possible effects of inbreeding, such as congenital birth defects. The chances of such disorders are increased when the biological parents are more closely related. This is because such pairings have a 25% probability of producing homozygous zygotes, resulting in offspring with two recessive alleles, which can produce disorders when these alleles are deleterious. [14] Because most recessive alleles are rare in populations, it is unlikely that two unrelated marriage partners will both be carriers of the same deleterious allele however, because close relatives share a large fraction of their alleles, the probability that any such deleterious allele is inherited from the common ancestor through both parents is increased dramatically. For each homozygous recessive individual formed there is an equal chance of producing a homozygous dominant individual — one completely devoid of the harmful allele. Contrary to common belief, inbreeding does not in itself alter allele frequencies, but rather increases the relative proportion of homozygotes to heterozygotes however, because the increased proportion of deleterious homozygotes exposes the allele to natural selection, in the long run its frequency decreases more rapidly in inbred populations. In the short term, incestuous reproduction is expected to increase the number of spontaneous abortions of zygotes, perinatal deaths, and postnatal offspring with birth defects. [15] The advantages of inbreeding may be the result of a tendency to preserve the structures of alleles interacting at different loci that have been adapted together by a common selective history. [16]

Malformations or harmful traits can stay within a population due to a high homozygosity rate, and this will cause a population to become fixed for certain traits, like having too many bones in an area, like the vertebral column of wolves on Isle Royale or having cranial abnormalities, such as in Northern elephant seals, where their cranial bone length in the lower mandibular tooth row has changed. Having a high homozygosity rate is problematic for a population because it will unmask recessive deleterious alleles generated by mutations, reduce heterozygote advantage, and it is detrimental to the survival of small, endangered animal populations. [17] When deleterious recessive alleles are unmasked due to the increased homozygosity generated by inbreeding, this can cause inbreeding depression. [18]

There may also be other deleterious effects besides those caused by recessive diseases. Thus, similar immune systems may be more vulnerable to infectious diseases (see Major histocompatibility complex and sexual selection). [19]

Inbreeding history of the population should also be considered when discussing the variation in the severity of inbreeding depression between and within species. With persistent inbreeding, there is evidence that shows that inbreeding depression becomes less severe. This is associated with the unmasking and elimination of severely deleterious recessive alleles. However, inbreeding depression is not a temporary phenomenon because this elimination of deleterious recessive alleles will never be complete. Eliminating slightly deleterious mutations through inbreeding under moderate selection is not as effective. Fixation of alleles most likely occurs through Muller's ratchet, when an asexual population's genome accumulates deleterious mutations that are irreversible. [20]

Despite all its disadvantages, inbreeding can also have a variety of advantages, such as reducing the recombination load, [21] and allowing the expression of recessive advantageous phenotypes. It has been proposed that under circumstances when the advantages of inbreeding outweigh the disadvantages, preferential breeding within small groups could be promoted, potentially leading to speciation. [22]

Autosomal recessive disorders occur in individuals who have two copies of an allele for a particular recessive genetic mutation. [23] Except in certain rare circumstances, such as new mutations or uniparental disomy, both parents of an individual with such a disorder will be carriers of the gene. These carriers do not display any signs of the mutation and may be unaware that they carry the mutated gene. Since relatives share a higher proportion of their genes than do unrelated people, it is more likely that related parents will both be carriers of the same recessive allele, and therefore their children are at a higher risk of inheriting an autosomal recessive genetic disorder. The extent to which the risk increases depends on the degree of genetic relationship between the parents the risk is greater when the parents are close relatives and lower for relationships between more distant relatives, such as second cousins, though still greater than for the general population. [24]

Children of parent-child or sibling-sibling unions are at an increased risk compared to cousin-cousin unions. [25] : 3 Inbreeding may result in a greater than expected phenotypic expression of deleterious recessive alleles within a population. [26] As a result, first-generation inbred individuals are more likely to show physical and health defects, [27] [28] including:

  • Reduced fertility both in litter size and sperm viability
  • Increased genetic disorders
  • Fluctuating facial asymmetry
  • Lower birth rate
  • Higher infant mortality and child mortality[29]
  • Smaller adult size
  • Loss of immune system function
  • Increased cardiovascular risks[30]

The isolation of a small population for a period of time can lead to inbreeding within that population, resulting in increased genetic relatedness between breeding individuals. Inbreeding depression can also occur in a large population if individuals tend to mate with their relatives, instead of mating randomly.

Many individuals in the first generation of inbreeding will never live to reproduce. [31] Over time, with isolation, such as a population bottleneck caused by purposeful (assortative) breeding or natural environmental factors, the deleterious inherited traits are culled. [6] [7] [32]

Island species are often very inbred, as their isolation from the larger group on a mainland allows natural selection to work on their population. This type of isolation may result in the formation of race or even speciation, as the inbreeding first removes many deleterious genes, and permits the expression of genes that allow a population to adapt to an ecosystem. As the adaptation becomes more pronounced, the new species or race radiates from its entrance into the new space, or dies out if it cannot adapt and, most importantly, reproduce. [33]

The reduced genetic diversity, for example due to a bottleneck will unavoidably increase inbreeding for the entire population. This may mean that a species may not be able to adapt to changes in environmental conditions. Each individual will have similar immune systems, as immune systems are genetically based. When a species becomes endangered, the population may fall below a minimum whereby the forced interbreeding between the remaining animals will result in extinction.

Natural breedings include inbreeding by necessity, and most animals only migrate when necessary. In many cases, the closest available mate is a mother, sister, grandmother, father, brother, or grandfather. In all cases, the environment presents stresses to remove from the population those individuals who cannot survive because of illness. [ citation needed ]

There was an assumption [ by whom? ] that wild populations do not inbreed this is not what is observed in some cases in the wild. However, in species such as horses, animals in wild or feral conditions often drive off the young of both sexes, thought to be a mechanism by which the species instinctively avoids some of the genetic consequences of inbreeding. [34] In general, many mammal species, including humanity's closest primate relatives, avoid close inbreeding possibly due to the deleterious effects. [25] : 6

Examples Edit

Although there are several examples of inbred populations of wild animals, the negative consequences of this inbreeding are poorly documented. [ citation needed ] In the South American sea lion, there was concern that recent population crashes would reduce genetic diversity. Historical analysis indicated that a population expansion from just two matrilineal lines was responsible for most of the individuals within the population. Even so, the diversity within the lines allowed great variation in the gene pool that may help to protect the South American sea lion from extinction. [35]

In lions, prides are often followed by related males in bachelor groups. When the dominant male is killed or driven off by one of these bachelors, a father may be replaced by his son. There is no mechanism for preventing inbreeding or to ensure outcrossing. In the prides, most lionesses are related to one another. If there is more than one dominant male, the group of alpha males are usually related. Two lines are then being "line bred". Also, in some populations, such as the Crater lions, it is known that a population bottleneck has occurred. Researchers found far greater genetic heterozygosity than expected. [36] In fact, predators are known for low genetic variance, along with most of the top portion of the trophic levels of an ecosystem. [37] Additionally, the alpha males of two neighboring prides can be from the same litter one brother may come to acquire leadership over another's pride, and subsequently mate with his 'nieces' or cousins. However, killing another male's cubs, upon the takeover, allows the new selected gene complement of the incoming alpha male to prevail over the previous male. There are genetic assays being scheduled for lions to determine their genetic diversity. The preliminary studies show results inconsistent with the outcrossing paradigm based on individual environments of the studied groups. [36]

In Central California, sea otters were thought to have been driven to extinction due to over hunting, until a small colony was discovered in the Point Sur region in the 1930s. [38] Since then, the population has grown and spread along the central Californian coast to around 2,000 individuals, a level that has remained stable for over a decade. Population growth is limited by the fact that all Californian sea otters are descended from the isolated colony, resulting in inbreeding. [39]

Cheetahs are another example of inbreeding. Thousands of years ago the cheetah went through a population bottleneck that reduced its population dramatically so the animals that are alive today are all related to one another. A consequence from inbreeding for this species has been high juvenile mortality, low fecundity, and poor breeding success. [40]

In a study on an island population of song sparrows, individuals that were inbred showed significantly lower survival rates than outbred individuals during a severe winter weather related population crash. These studies show that inbreeding depression and ecological factors have an influence on survival. [20]

A measure of inbreeding of an individual A is the probability F(A) that both alleles in one locus are derived from the same allele in an ancestor. These two identical alleles that are both derived from a common ancestor are said to be identical by descent. This probability F(A) is called the "coefficient of inbreeding". [41]

Another useful measure that describes the extent to which two individuals are related (say individuals A and B) is their coancestry coefficient f(A,B), which gives the probability that one randomly selected allele from A and another randomly selected allele from B are identical by descent. [42] This is also denoted as the kinship coefficient between A and B. [43]

A particular case is the self-coancestry of individual A with itself, f(A,A), which is the probability that taking one random allele from A and then, independently and with replacement, another random allele also from A, both are identical by descent. Since they can be identical by descent by sampling the same allele or by sampling both alleles that happen to be identical by descent, we have f(A,A) = 1/2 + F(A)/2. [44]

Both the inbreeding and the coancestry coefficients can be defined for specific individuals or as average population values. They can be computed from genealogies or estimated from the population size and its breeding properties, but all methods assume no selection and are limited to neutral alleles.

There are several methods to compute this percentage. The two main ways are the path method [45] [41] and the tabular method. [46] [47]

Typical coancestries between relatives are as follows:

  • Father/daughter or mother/son → 25% ( 1 ⁄ 4 )
  • Brother/sister → 25% (
  • 1 ⁄ 4 )
  • Grandfather/granddaughter or grandmother/grandson → 12.5% (
  • 1 ⁄ 8 )
  • Half-brother/half-sister, Double cousins → 12.5% (
  • 1 ⁄ 8 )
  • Uncle/niece or aunt/nephew → 12.5% (
  • 1 ⁄ 8 )
  • Great-grandfather/great-granddaughter or great-grandmother/great-grandson → 6.25% (
  • 1 ⁄ 16 )
  • Half-uncle/niece or half-aunt/nephew → 6.25% (
  • 1 ⁄ 16 )
  • First cousins → 6.25% (
  • 1 ⁄ 16 )

Wild animals Edit

    females regularly mate with their fathers and brothers. [48] : North Carolina State University found that bedbugs, in contrast to most other insects, tolerate incest and are able to genetically withstand the effects of inbreeding quite well. [49] females prefer to mate with their own brothers over unrelated males. [1] : 'It turns out that females in these hermaphrodite insects are not really fertilizing their eggs themselves, but instead are having this done by a parasitic tissue that infects them at birth,' says Laura Ross of Oxford University's Department of Zoology. ‘It seems that this infectious tissue derives from left-over sperm from their father, who has found a sneaky way of having more children by mating with his daughters.' [50]
  • Adactylidium: The single male offspring mite mates with all the daughters when they are still in the mother. The females, now impregnated, cut holes in their mother's body so that they can emerge to find new thrips eggs. The male emerges as well, but does not look for food or new mates, and dies after a few hours. The females die at the age of 4 days, when their own offspring eat them alive from the inside. [51]

Semi-domestic animals Edit

Domestic animals Edit

Breeding in domestic animals is primarily assortative breeding (see selective breeding). Without the sorting of individuals by trait, a breed could not be established, nor could poor genetic material be removed. Homozygosity is the case where similar or identical alleles combine to express a trait that is not otherwise expressed (recessiveness). Inbreeding exposes recessive alleles through increasing homozygosity. [55]

Breeders must avoid breeding from individuals that demonstrate either homozygosity or heterozygosity for disease causing alleles. [56] The goal of preventing the transfer of deleterious alleles may be achieved by reproductive isolation, sterilization, or, in the extreme case, culling. Culling is not strictly necessary if genetics are the only issue in hand. Small animals such as cats and dogs may be sterilized, but in the case of large agricultural animals, such as cattle, culling is usually the only economic option.

The issue of casual breeders who inbreed irresponsibly is discussed in the following quotation on cattle:

Meanwhile, milk production per cow per lactation increased from 17,444 lbs to 25,013 lbs from 1978 to 1998 for the Holstein breed. Mean breeding values for milk of Holstein cows increased by 4,829 lbs during this period. [57] High producing cows are increasingly difficult to breed and are subject to higher health costs than cows of lower genetic merit for production (Cassell, 2001).

Intensive selection for higher yield has increased relationships among animals within breed and increased the rate of casual inbreeding.

Many of the traits that affect profitability in crosses of modern dairy breeds have not been studied in designed experiments. Indeed, all crossbreeding research involving North American breeds and strains is very dated (McAllister, 2001) if it exists at all. [58]

The BBC produced two documentaries on dog inbreeding titled Pedigree Dogs Exposed and Pedigree Dogs Exposed: Three Years On that document the negative health consequences of excessive inbreeding.

Linebreeding Edit

Linebreeding is a form of inbreeding. There is no clear distinction between the two terms, but linebreeding may encompass crosses between individuals and their descendants or two cousins. [54] [59] This method can be used to increase a particular animal's contribution to the population. [54] While linebreeding is less likely to cause problems in the first generation than does inbreeding, over time, linebreeding can reduce the genetic diversity of a population and cause problems related to a too-small gene pool that may include an increased prevalence of genetic disorders and inbreeding depression. [ citation needed ]

Outcrossing Edit

Outcrossing is where two unrelated individuals are crossed to produce progeny. In outcrossing, unless there is verifiable genetic information, one may find that all individuals are distantly related to an ancient progenitor. If the trait carries throughout a population, all individuals can have this trait. This is called the founder effect. In the well established breeds, that are commonly bred, a large gene pool is present. For example, in 2004, over 18,000 Persian cats were registered. [60] A possibility exists for a complete outcross, if no barriers exist between the individuals to breed. However, it is not always the case, and a form of distant linebreeding occurs. Again it is up to the assortative breeder to know what sort of traits, both positive and negative, exist within the diversity of one breeding. This diversity of genetic expression, within even close relatives, increases the variability and diversity of viable stock.

Laboratory animals Edit

Systematic inbreeding and maintenance of inbred strains of laboratory mice and rats is of great importance for biomedical research. The inbreeding guarantees a consistent and uniform animal model for experimental purposes and enables genetic studies in congenic and knock-out animals. In order to achieve a mouse strain that is considered inbred, a minimum of 20 sequential generations of sibling matings must occur. With each successive generation of breeding, homozygosity in the entire genome increases, eliminating heterozygous loci. With 20 generations of sibling matings, homozygosity is occurring at roughly 98.7% of all loci in the genome, allowing for these offspring to serve as animal models for genetic studies. [61] The use of inbred strains is also important for genetic studies in animal models, for example to distinguish genetic from environmental effects. The mice that are inbred typically show considerably lower survival rates.

Effects Edit

Inbreeding increases homozygosity, which can increase the chances of the expression of deleterious recessive alleles and therefore has the potential to decrease the fitness of the offspring. With continuous inbreeding, genetic variation is lost and homozygosity is increased, enabling the expression of recessive deleterious alleles in homozygotes. The coefficient of inbreeding, or the degree of inbreeding in an individual, is an estimate of the percent of homozygous alleles in the overall genome. [63] The more biologically related the parents are, the greater the coefficient of inbreeding, since their genomes have many similarities already. This overall homozygosity becomes an issue when there are deleterious recessive alleles in the gene pool of the family. [64] By pairing chromosomes of similar genomes, the chance for these recessive alleles to pair and become homozygous greatly increases, leading to offspring with autosomal recessive disorders. [64]

Inbreeding is especially problematic in small populations where the genetic variation is already limited. [65] By inbreeding, individuals are further decreasing genetic variation by increasing homozygosity in the genomes of their offspring. [66] Thus, the likelihood of deleterious recessive alleles to pair is significantly higher in a small inbreeding population than in a larger inbreeding population. [65]

The fitness consequences of consanguineous mating have been studied since their scientific recognition by Charles Darwin in 1839. [67] [68] Some of the most harmful effects known from such breeding includes its effects on the mortality rate as well as on the general health of the offspring. [69] Since the 1960s, there have been many studies to support such debilitating effects on the human organism. [66] [67] [69] [70] [71] Specifically, inbreeding has been found to decrease fertility as a direct result of increasing homozygosity of deleterious recessive alleles. [71] [72] Fetuses produced by inbreeding also face a greater risk of spontaneous abortions due to inherent complications in development. [73] Among mothers who experience stillbirths and early infant deaths, those that are inbreeding have a significantly higher chance of reaching repeated results with future offspring. [74] Additionally, consanguineous parents possess a high risk of premature birth and producing underweight and undersized infants. [75] Viable inbred offspring are also likely to be inflicted with physical deformities and genetically inherited diseases. [63] Studies have confirmed an increase in several genetic disorders due to inbreeding such as blindness, hearing loss, neonatal diabetes, limb malformations, disorders of sex development, schizophrenia and several others. [63] [76] Moreover, there is an increased risk for congenital heart disease depending on the inbreeding coefficient (See coefficient of inbreeding) of the offspring, with significant risk accompanied by an F =.125 or higher. [27]

Prevalence Edit

The general negative outlook and eschewal of inbreeding that is prevalent in the Western world today has roots from over 2000 years ago. Specifically, written documents such as the Bible illustrate that there have been laws and social customs that have called for the abstention from inbreeding. Along with cultural taboos, parental education and awareness of inbreeding consequences have played large roles in minimizing inbreeding frequencies in areas like Europe. That being so, there are less urbanized and less populated regions across the world that have shown continuity in the practice of inbreeding.

The continuity of inbreeding is often either by choice or unavoidably due to the limitations of the geographical area. When by choice, the rate of consanguinity is highly dependent on religion and culture. [65] In the Western world some Anabaptist groups are highly inbred because they originate from small founder populations and until [ clarification needed ] today [ when? ] marriage outside the groups is not allowed for members. [ citation needed ] Especially the Reidenbach Old Order Mennonites [77] and the Hutterites stem from very small founder populations. The same is true for some Hasidic and Haredi Jewish groups.

Of the practicing regions, Middle Eastern and northern Africa territories show the greatest frequencies of consanguinity. [65] The link between the high frequency and the region is primarily due to the dominance of Islamic populations, who have historically engaged in familyline relations. [68] However, inbreeding culture in Middle East didn't begin with Islam, having roots in ancient Egypt and Mesopotamia.

Among these populations with high levels of inbreeding, researchers have found several disorders prevalent among inbred offspring. In Lebanon, Saudi Arabia, Egypt, and in Israel, the offspring of consanguineous relationships have an increased risk of congenital malformations, congenital heart defects, congenital hydrocephalus and neural tube defects. [65] Furthermore, among inbred children in Palestine and Lebanon, there is a positive association between consanguinity and reported cleft lip/palate cases. [65] Historically, populations of Qatar have engaged in consanguineous relationships of all kinds, leading to high risk of inheriting genetic diseases. As of 2014, around 5% of the Qatari population suffered from hereditary hearing loss most were descendants of a consanguineous relationship. [78]

Novel Graphical Analyses of Runs of Homozygosity among Species and Livestock Breeds

Runs of homozygosity (ROH), uninterrupted stretches of homozygous genotypes resulting from parents transmitting identical haplotypes to their offspring, have emerged as informative genome-wide estimates of autozygosity (inbreeding). We used genomic profiles based on 698 K single nucleotide polymorphisms (SNPs) from nine breeds of domestic cattle (Bos taurus) and the European bison (Bison bonasus) to investigate how ROH distributions can be compared within and among species. We focused on two length classes: 0.5–15 Mb to investigate ancient events and >15 Mb to address recent events (approximately three generations). For each length class, we chose a few chromosomes with a high number of ROH, calculated the percentage of times a SNP appeared in a ROH, and plotted the results. We selected areas with distinct patterns including regions where (1) all groups revealed an increase or decrease of ROH, (2) bison differed from cattle, (3) one cattle breed or groups of breeds differed (e.g., dairy versus meat cattle). Examination of these regions in the cattle genome showed genes potentially important for natural and human-induced selection, concerning, for example, meat and milk quality, metabolism, growth, and immune function. The comparative methodology presented here permits visual identification of regions of interest for selection, breeding programs, and conservation.

1. Introduction

Mating among closely related individuals can affect the fitness of the progeny by increasing the inbreeding coefficient (F) [1] and therefore the probability that alleles at a locus, sampled randomly in a population, are identical by descent (IBD) [2]. The reduction in fitness can be due to the accumulation of recessive lethal genetic disorders, reduction of fertility, and lower adaptive potential [1, 3, 4].

In wild living and captive populations, there is an urgent need to reduce inbreeding and augment genetic diversity, and this can be achieved by implementing carefully planned mating strategies. One possibility consists in reducing the level of inbreeding per generation and the response to selection (optimal contribution selection) [5]. The estimation of F requires completeness and accuracy of the available pedigree records, which are not always available, because of missing information or registration errors. When genotypes are available a probabilistic approach can be utilized for the reconstruction of the pedigree. However, such an approach does not take into account the stochastic nature of recombination [6]. New approaches based on the runs of homozygosity (ROH), which are DNA segments that harbour uninterrupted stretches of homozygous genotypes, have shown to be reliable estimates of autozygosity at the genome-wide level [7–9].

In addition, the frequency and extent of ROH can be used to estimate the time when the inbreeding event took place. Considering that recombination events break long chromosome segments, it is assumed that long autozygous segments in an individual derive from a common recent ancestor, whereas shorter autozygous segments are indicating a remote common ancestor [10–12]. We should therefore expect that the longer the homozygous segments, the more recent the inbreeding. However, long ROH may also be explained by a recent event under strong selective pressure. ROH can thus be used to identify the genomic signatures of recent and/or ancient selective pressure, as shown by [9]. Additionally, fixed ROH in all the individuals in a population could indicate past selective events. Clearly, the presence of long ROH at relatively high frequency in a population could also indicate the presence of genetic substructure, with consanguineous mating occurring only within some subpopulations [13]. ROH are also affected by demographic events [8] and further investigation should examine issues such as skewed reproductive success.

The objective of this study was to describe and compare the distribution of ROH of different length in nine Bos taurus cattle breeds under different management practices and selection histories. The same comparison was made at the interspecific level by comparing the distribution of the ROH between the abovementioned cattle breeds and the Lowland line of the European bison (Bison bonasus) from the Białowieża National Park (Poland). The Lowland line is highly inbred due to only seven founders [14].

While previous investigations were exclusively based on the count and sum of the number of ROH above a given length [9], in this paper we analysed the frequency of SNPs falling within a ROH above and below an a priori chosen length (15 Mb) and we visualized the different distributions across populations. In addition, this graphical visualization allows the identification of similarities and dissimilarities in the regions that can be used to investigate possible adaptive/selective patterns.

2. Material and Methods

2.1. Genotypes and Quality Control

Genotypes consisting of 777,972 single nucleotide polymorphisms (SNPs) from the BovineHD BeadChip (Illumina Inc., San Diego, CA) were generated for 891 sires of multiple breeds. Breeds represented include Angus (

), Holstein-Friesian crosses ( ), Limousin ( ), and Simmental (

) (data from [9]). Angus, Belgian Blue, and Hereford are primarily meat breeds Friesian, Holstein, and Holstein-Friesian crosses are primarily dairy breeds, while Limousin, Simmental, and Charolais are used for both milk and meat. Forty European Lowland bison (Bison bonasus) from Białowieża National Park (Poland) were used for comparison. GenomeStudio™ (Illumina Inc., San Diego, CA) and accompanying guidelines from Illumina (http://www.illumina.com/Documents/products/technotes/technote_infinium_genotyping_data_analysis.pdf) were used for quality control. Total individual call rate in the bison was 0.99. For cattle, only biallelic SNPs on the 29 autosomes were retained after removing all monomorphic SNPs across breeds, filtering for Hardy Weinberg Equilibrium (

) within each breed separately and for call rates >90%. Final analyses were performed on 867 cattle and 40 bison with 698,384 SNPs.

2.2. Runs of Homozygosity

Following the approach in [9], ROH were estimated using PLINK v1.07 [15] and were defined within a sliding window of 50 SNPs, in one SNP interval, across the genome. Up to one possible heterozygous genotype was permitted and no more than two SNPs with missing genotypes were allowed per window (see [9]).

ROH were divided in seven length categories (1–5 Mb, 5–10 Mb, 10–15 Mb, 15–20 Mb, 20–25 MB, 25–30 Mb, and >30 Mb). For each ROH length category we summed all ROH per animal and averaged this per cattle breed and for the bison. In order to investigate the potential of our approach, we then focused on two length classes: from 500 Kb till 15 Mb to investigate ancient events and >15 Mb to address recent events. To select target chromosomes for detailed analyses, we created Manhattan plots with SAS 9.4 (SAS Institute Inc., Toronto, Canada) for both length classes and selected the chromosomes accordingly. For the chosen chromosomes, we calculated the percentage of times a SNP appeared in a ROH and plotted these results with SAS.

2.3. Analyses of Genomic Regions in the Runs of Homozygosity

As an example for the methodology applied in this study, we selected regions of the different chromosomes that showed one of the following patterns (see Figure 2): (a) a simultaneous increase (or decrease) in the number of SNPs in a ROH across all populations, as this pattern could possibly involve genes fundamental for the two species analysed (b) few populations showing an opposite pattern compared to the others, as this could comprise genes specific for those populations (c) different patterns between dairy and meat breeds, as this could possibly concern regions under human-induced directional selection (d) different patterns between bison and domestic cattle breeds, as this pattern may be related to traits important for survival in the wild (e) a single domestic breed differentiating from the others, as this could relate to specific characteristics of that breed (f) a long region with a high percentage of ROH, as this could be associated with recent selective events (g) a short region with opposite trend within a longer homogeneous region, to investigate what could have caused such an abrupt change in variability levels. Each region was screened using NCBI (https://www.ncbi.nlm.nih.gov/) resources for the presence of annotated genes (release 104) and information on their biological function and possible evolutionary importance.

3. Results

3.1. Runs of Homozygosity

The European bison exhibited the highest mean sum of ROH in the length categories 1–5 Mb, 5-10 Mb, and 10–15 Mb compared to all the domestic breeds. Angus and Hereford also showed considerably higher mean sums than other breeds in the categories 1–5 Mb and 5–10 Mb (see Figure 1).

In the Manhattan plot for the length class between 500 Kb and 15 Mb, chromosomes 2 and 3 showed a group of extremely variable SNPs, while chromosomes 7, 14, and 16 had the highest density and frequencies of SNPs falling in a ROH (see Figure S1a in Supplementary Material available online at http://dx.doi.org/10.1155/2016/2152847). We thus focused on these chromosomes for subsequent analyses. For the ROH >15 Mb, the Manhattan plot showed a more homogeneous distribution but we selected chromosomes 6, 9, and 20 for subsequent analyses (Figure S2a). In the plots based on ROH < 15 Mb, we observed large regions of the bison genome where almost 100% of SNPs fell within a ROH (Figure S1b–f). The frequency of SNPs falling in a ROH > 15 Mb was lower for all populations, in accordance with the smaller number of ROH in this length category (Figure S2b–d). Additionally, the frequency of a SNP falling within a ROH in the bison was not higher than that observed in the domestic breeds with a single exception on chromosome 9 (Figure S2c). On chromosome 20 the highest percentage of SNPs falling within a ROH was detected in dairy cattle breeds (Figure S2d). No clear pattern was observed on chromosome 6 (Figure S2b).

3.2. Analyses of Genomic Regions in the Runs of Homozygosity

The in-depth analysis of 17 regions, selected from seven chromosomes (i.e., 2, 3, 7, 9, 14, 16, and 20) led to the identification of more than 300 annotated genes whose functions vary considerably (see Table S1). The most frequent functionally characterised genes were those related to metabolic pathways, but we also observed genes related to disease and immune function, growth, and reproduction. As an example, we review here a few of our observations in the selected regions.

In summary, pattern (a) were mainly related to metabolic pathways, involving several CD-, ATP-, and SLAM-family genes (see Table S1) and olfactory receptors. Metabolic pathways were the main genes observed in pattern (b). Pattern (c) was inconclusive for ROH < 15 Mb. In pattern (f) (also an example of (c)) ROH > 15 Mb included genes related to milk and meat quality, growth, and metabolic disorders related to energy unbalanced consumption. Patterns (d) were located in portions of the chromosomes poorly described, with the only exception being the long region on chromosome 9, where a high number of ROH > 15 Mb was observed (Figure S2c). In addition to the metabolism and disease related genes widely encountered in all the screened regions, we report the presence of genes related to olfactory perception, obesity, growth, and sperm malformation in this region. In pattern (e), we observed a region (Figure 2(e)) where the Simmental showed higher variability than the other breeds. Here, genes involved were related to fat thickness and colour, growth, and sperm functionality. In pattern (f), where Hereford showed extremely high frequency values of SNP falling within a ROH and the Belgian Blue extreme variability (with the other breeds in between Figure S1f, near 45000000), the genes observed were mainly related to the codification of proteins involved in sugar transport and assimilation at cellular level. In pattern (g) we observed genes involved in cortisol pathways and sweet perception, regulation of host response to virus infection, and regulatory function in ovulation.

4. Discussion

Our findings revealed several chromosomes with a high number of ROH, and most results concerned ROH < 15 Mb. Upon closer inspection of selected chromosomes, we observed genes potentially important for natural and human-induced selection, concerning, for example, meat and milk quality, metabolism, growth, and immune function. Hence, the ROH approach appears informative for evaluating and comparing species and population history and evaluating possible patterns of adaptation.

We observed comparatively few results for ROH > 15 Mb, the longer regions that are likely to reflect recent inbreeding [9, 11]. Our results may thus suggest relatively limited recent inbreeding in the cattle breeds included in the study, although the many shorter ROH could indicate a lower

in the past [16]. For the European bison, however, large regions of the genome had a 100% (or near 100%) frequency of SNPs falling within a ROH. This suggests high levels of inbreeding, which is consistent with earlier studies and known population history involving a severe bottleneck [17, 18]. However, even limited inbreeding can cause detrimental effects [1, 19] and should be monitored. Earlier studies across species have suggested that ROH > 16 Mb may be considered as recent inbreeding [11, 16]. Analyses of cattle breeds report ROH > 16 Mb as the expected mean after approximately three generations since the most recent common ancestor, whereas autozygosity due to more distant common ancestors will not be captured by this measure [11]. For an in-depth assessment of inbreeding, it may be necessary to investigate different ROH length classes considering the history of the organisms under study. For example, comparisons between wild and domestic species may show different patterns than native and commercial livestock in terms of recent and/or past histories of inbreeding. Consequently, ROH length classes should be assessed on a case by case basis with exploratory analyses informed, where possible, by the history of the species under study.

Variation in sample size and may have influenced the results. Our comparison of, for example, Belgian Blue ( ) and Holstein ( ) should therefore be interpreted with caution. Other important factors that may play a role are differences in breed genetic diversity. McTavish et al. [20] reported observed heterozygosity for several breeds included in our study based on 50 K SNP markers. Among the breeds that showed distinct ROH patterns in our study, they note that Simmental showed a heterozygosity of 0.28 ( ), the Belgian Blue 0.30 ( ), the Hereford 0.29 ( ), and the Holstein 0.30 ( ). Furthermore, the value for Limousin was 0.29 ( ) and for Charolais was 0.31 ( ). Although these values are similar despite variable sample size, among- and within-breed variation in genetic diversity could affect ROH results and their interpretation and may therefore complicate our comparison of cattle breeds and European bison.

Angus and Hereford breeds, together with bison, show high mean sum of ROH in the length class 1–10 Mb, which may be a result of ancestral relatedness owing to small founder populations and isolated origins [11]. In particular, the ROH for the bison is extremely high for the intervals 1–5 Mb and 5–10 Mb with several regions that are completely fixed. This appears consistent with an estimated of 23 and a total of seven founders for the European bison’s Lowland population [18]. In comparison, a recent survey presented considerably larger but variable census population size (

) and for some of the cattle breeds included in our study [21]. For Aberdeen Angus, they reported > 10 M and of 136. For Holstein, was >65 M and was 99, whereas for Limousin, was >4 M and was 174. There may thus be considerable differences in population history among breeds and also for breeds within the same group (such as meat production), which could have affected our results.

We observed genes grouped into various functional categories. The types of genes observed may reveal adaptive patterns and indicate human-induced and/or natural selection, for example, in cases of genes linked to growth and immunity where the first is likely to be human-modified and the second is subject to stronger natural selection. Our results also highlight the need to consider potential conflicts between these two sources of selection. For example, we noted a gene implicated in ketosis (region F, chromosome 20), a metabolic disorder that occurs in cattle when energy demands such as high milk production exceed energy intake and result in a negative energy balance. Strong directional selection for high-performance characteristics such as high milk yield may therefore have implications for animal health and welfare, life expectancy, and the ethical dimensions of animal breeding to cope with their living environments (see, e.g., [22, 23]).

4.1. Applications

The ROH approach seems informative for investigating selection and evolutionary histories across a range of different populations, including wild/domestic species, native/commercial livestock, and commercial breeds of various kinds (e.g., cattle breeds for milk or meat, sheep breeds for meat or wool). Our study compared cattle with one related wild species, the European bison. However, this species is highly inbred and has low genetic diversity [18]. Study of other wild-domestic species pairs may therefore provide a more nuanced picture of genomic regions under selection, for example, in domestic pigs and wild boar, or captive and free-living populations of the wild boar (e.g., [24]), thus taking advantage of recent developments in high-density genomic arrays to investigate domestic and wild species (e.g., [25]).

The results of our analyses may also suggest applications for genetic rescue. This could include key genetic regions of high variability observed in one breed, which could be transferred to one or more other populations, for example, related to immune system function or tolerance to environmental factors such as heat, parasites, and infectious disease [26, 27]. Moreover, genes related to growth may have important applications for animal breeding and could be introduced to new breeds to enhance both genetic variation and production [28]. Further research may also help clarify the extent to which selection for rapid growth might conflict with selection for meat quality, which may be relevant to conservation management and breeding for both commercial and native livestock breeds (e.g., [29]).

It will be important to establish whether ROH are under selection. If a ROH is not under selection, its length should normally decrease with every generation as the expected length of autozygous segments identical by descent follows an exponential distribution with mean equal to 0.5

Morgans, where is the number of generations since the common ancestor [30]. Conversely, a ROH could contain recessive variants that are expressed in the autozygous state. These variants are known to cause various genetic diseases in humans as a result of specific mutations (e.g., phenylketonuria, Tay-Sachs disease, and cystic fibrosis) and may also be involved in complex diseases such as heart and liver diseases and diabetes [31].

For livestock, the incidence of disease associated with intensive production has increased among several breeds [32], such as Holstein and Jersey [33–35]. Additionally, important traits, such as adaptation to low-quality food resources, parasites, and tolerance to disease and temperature fluctuations may be found mostly in native breeds [36]. An important aspect of the ROH assessment will be identification of genetic variants with applications for genetic rescue, which could benefit both native and commercial breeds [28] to increase robustness and tolerance to environmental variation [27, 36].

4.2. Possible Limiting Factors

Ascertainment bias could have affected the comparison of ROH between different species (here cattle and bison) [37]. Moreover, our observations are necessarily incomplete, as there are still large regions of the genome that have not been fully described, as testified by the high number of uncharacterised genes we encountered in our screening (see Table S1). However, key genomic regions can be noted for further research, which also helps identify high-priority areas of the genome for future study.

5. Conclusions

The comparative methodology presented here permits visual identification of regions of interest, which could be of value for selection and breeding programs. The ROH approach offers several immediate applications. Firstly, breeding strategies may be improved by reduction in ROH that are acting to reduce genomic diversity. Such a strategy could be useful where genomic regions have lost important diversity or been accidentally fixed, for example, as a consequence of a population bottleneck and/or founder effect. Further, the ROH approach has implications for genetic rescue and the design of breeding strategies for populations at risk. The presence of ROH at intermediate frequency in a population may indicate heterogeneity of the in different genomic regions. Accordingly, a breeding strategy based on maximising for a population could produce an increase of for some chromosomal regions and a reduction in others. This situation could complicate the design of a long-term protocol because of the risk of fixation of certain genes and loss of genetic diversity. Human-driven breeding could also overwhelm natural selective pressures, especially for populations mainly governed by genetic drift due to the small . It is therefore necessary to balance various considerations for long-term conservation breeding, and information from ROH can help pinpoint important genomic regions even if we do not, at the moment, have a complete understanding of their function.

Competing Interests

The authors declare that they have no competing interests.

Authors’ Contributions

Laura Iacolina and Astrid V. Stronen contributed equally.


Cino Pertoldi was supported by a grant from Danish Natural Science Research Council (Grant nos. 11-103926, 09-065999, and 95095995), the Carlsberg Foundation (Grant no. 2011-01-0059), and the Aalborg Zoo Conservation Foundation (AZCF). Laura Iacolina has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Action (Grant Agreement no. 656697). Astrid V. Stronen received funding from the Danish Natural Science Research Council (Postdoctoral Grant 1337-00007).

Supplementary Materials

FIGURE S1: Manhattan plot and plots of frequency of SNP in a ROH in the range 500Kb - 15Mb. Chromosomes 2, 3, 7, 14 and 16 are shown. FIGURE S2: Manhattan plot and plots of frequency of SNP in a ROH in the range > 15Mb. Chromosomes 6, 9 and 20 are shown. TABLE S1: Summary table showing the genes identified in the screened regions, their function and NCBI description.


  1. D. W. Bjelland, K. A. Weigel, N. Vukasinovic, and J. D. Nkrumah, “Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding,” Journal of Dairy Science, vol. 96, no. 7, pp. 4697–4706, 2013. View at: Publisher Site | Google Scholar
  2. S. Wright, “Coefficients of inbreeding and relationship,” The American Naturalist, vol. 56, no. 645, pp. 330–338, 1922. View at: Publisher Site | Google Scholar
  3. O. González-Recio, E. López de Maturana, and J. P. Gutiérrez, “Inbreeding depression on female fertility and calving ease in spanish dairy cattle,” Journal of Dairy Science, vol. 90, no. 12, pp. 5744–5752, 2007. View at: Publisher Site | Google Scholar
  4. S. Sommer, “The importance of immune gene variability (MHC) in evolutionary ecology and conservation,” Frontiers in Zoology, vol. 2, article 16, 2005. View at: Publisher Site | Google Scholar
  5. G. Gandini, A. Stella, M. Del Corvo, and G. B. Jansen, “Selection with inbreeding control in simulated young bull schemes for local dairy cattle breeds,” Journal of Dairy Science, vol. 97, no. 3, pp. 1790–1798, 2014. View at: Publisher Site | Google Scholar
  6. R. McQuillan, A.-L. Leutenegger, R. Abdel-Rahman et al., “Runs of homozygosity in European populations,” The American Journal of Human Genetics, vol. 83, no. 3, pp. 359–372, 2008. View at: Publisher Site | Google Scholar
  7. J. Gibson, N. E. Morton, and A. Collins, “Extended tracts of homozygosity in outbred human populations,” Human Molecular Genetics, vol. 15, no. 5, pp. 789–795, 2006. View at: Publisher Site | Google Scholar
  8. M. Bosse, H.-J. Megens, O. Madsen et al., “Regions of homozygosity in the porcine genome: consequence of demography and the recombination landscape,” PLoS Genetics, vol. 8, no. 11, Article ID e1003100, 2012. View at: Publisher Site | Google Scholar
  9. D. C. Purfield, D. P. Berry, S. McParland, and D. G. Bradley, “Runs of homozygosity and population history in cattle,” BMC Genetics, vol. 13, article 70, 2012. View at: Publisher Site | Google Scholar
  10. M. Ferencakovic, E. Hamzic, B. Gredler, I. Curik, and J. Sölkner, “Runs of homozygosity reveal genomewide autozygosity in the Austrian Fleckvieh cattle,” Agriculturae Conspectus Scientificus, vol. 76, no. 4, pp. 325–328, 2011. View at: Google Scholar
  11. M. Ferenლković, E. Hamzić, B. Gredler et al., “Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations,” Journal of Animal Breeding and Genetics, vol. 130, no. 4, pp. 286–293, 2013. View at: Publisher Site | Google Scholar
  12. M. Ferenლković, J. Sölkner, and I. Curik, “Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors,” Genetics Selection Evolution, vol. 45, no. 1, article 42, 2013. View at: Publisher Site | Google Scholar
  13. L. Iacolina, M. Scandura, D. J. Goedbloed et al., “Genomic diversity and differentiation of a managed island wild boar population,” Heredity, vol. 116, no. 1, pp. 60–67, 2016. View at: Publisher Site | Google Scholar
  14. H. M. Slatis, “An analysis of inbreeding in the European bison,” Genetics, vol. 45, pp. 275–287, 1960. View at: Google Scholar
  15. S. Purcell, B. Neale, K. Todd-Brown et al., “Plink: a tool set for whole-genome association and population-based linkage analyses,” American Journal of Human Genetics, vol. 81, no. 3, pp. 559–575, 2007. View at: Publisher Site | Google Scholar
  16. M. Kirin, R. McQuillan, C. S. Franklin, H. Campbell, P. M. McKeigue, and J. F. Wilson, “Genomic runs of homozygosity record population history and consanguinity,” PLoS ONE, vol. 5, no. 11, Article ID e13996, 2010. View at: Publisher Site | Google Scholar
  17. K. Oleński, M. Tokarska, D. M. Hering et al., “Genome-wide association study for posthitis in the free-living population of European bison (Bison bonasus),” Biology Direct, vol. 10, no. 2, 2015. View at: Publisher Site | Google Scholar
  18. M. Tokarska, C. Pertoldi, R. Kowalczyk, and K. Perzanowski, “Genetic status of the European bison Bison bonasus after extinction in the wild and subsequent recovery,” Mammal Review, vol. 41, no. 2, pp. 151–162, 2011. View at: Publisher Site | Google Scholar
  19. J. E. Pryce, M. Haile-Mariam, M. E. Goddard, and B. J. Hayes, “Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle,” Genetics Selection Evolution, vol. 46, article 71, 2014. View at: Publisher Site | Google Scholar
  20. E. J. McTavish, J. E. Decker, R. D. Schnabel, J. F. Taylor, and D. M. Hillis, “New World cattle show ancestry from multiple independent domestication events,” Proceedings of the National Academy of Sciences of the United States of America, vol. 110, no. 15, pp. E1398–E1406, 2013. View at: Publisher Site | Google Scholar
  21. The Bovine HapMap Consortium, “Genome-wide survey of SNP variation uncovers the genetic structure of cattle breeds,” Science, vol. 324, no. 5926, pp. 528–532, 2009. View at: Publisher Site | Google Scholar
  22. W. M. Muir, H.-W. Cheng, and C. Croney, “Methods to address poultry robustness and welfare issues through breeding and associated ethical considerations,” Frontiers in Genetics, vol. 5, article 407, 2014. View at: Publisher Site | Google Scholar
  23. W. M. Rauw and L. Gomez-Raya, “Genotype by environment interaction and breeding for robustness in livestock,” Frontiers in Genetics, vol. 6, article 310, 2015. View at: Publisher Site | Google Scholar
  24. A. Canu, S. Costa, L. Iacolina, P. Piatti, M. Apollonio, and M. Scandura, “Are captive wild boar more introgressed than free-ranging wild boar? Two case studies in Italy,” European Journal of Wildlife Research, vol. 60, no. 3, pp. 459–467, 2014. View at: Publisher Site | Google Scholar
  25. V. R. Kharzinova, A. A. Sermyagin, E. A. Gladyr, I. M. Okhlopkov, G. Brem, and N. A. Zinovieva, “A study of applicability of SNP chips developed for bovine and ovine species to whole-genome analysis of reindeer Rangifer tarandus,” Journal of Heredity, vol. 106, no. 6, pp. 758–761, 2015. View at: Publisher Site | Google Scholar
  26. F. Alpay, Y. Zare, M. H. Kamalludin et al., “Genome-wide association study of susceptibility to infection by Mycobacterium avium subspecies paratuberculosis in Holstein cattle,” PLoS ONE, vol. 9, no. 12, Article ID e111704, 2014. View at: Publisher Site | Google Scholar
  27. L. R. Porto-Neto, A. Reverter, K. C. Prayaga et al., “The genetic architecture of climatic adaptation of tropical cattle,” PLoS ONE, vol. 9, no. 11, Article ID e113284, 2014. View at: Publisher Site | Google Scholar
  28. T. N. Kristensen, A. A. Hoffmann, C. Pertoldi, and A. V. Stronen, “What can livestock breeders learn from conservation genetics and vice versa?” Frontiers in Genetics, vol. 5, article 38, 2015. View at: Publisher Site | Google Scholar
  29. G. Holló, K. Nuernberg, T. Somogyi, I. Anton, and I. Holló, “Comparison of fattening performance and slaughter value of local Hungarian cattle breeds to international breeds,” Archiv für Tierzucht, vol. 55, no. 1, pp. 1–12, 2012. View at: Google Scholar
  30. D. P. Howrigan, M. A. Simonson, and M. C. Keller, “Detecting autozygosity through runs of homozygosity: a comparison of three autozygosity detection algorithms,” BMC Genomics, vol. 12, article 460, 2011. View at: Publisher Site | Google Scholar
  31. L. B. Andrews, J. E. Fullarton, N. A. Holtzman, and A. G. Motulsky, Assessing Genetic Risks: Implications for Health and Social Policy, National Academy Press, Washington, DC, USA, 1994.
  32. I. Medugorac, C. E. Veit-Kensch, J. Ramljak et al., “Conservation priorities of genetic diversity in domesticated metapopulations: a study in taurine cattle breeds,” Ecology and Evolution, vol. 1, no. 3, pp. 408–420, 2011. View at: Publisher Site | Google Scholar
  33. J. S. Agerholm, C. Bendixen, O. Andersen, and J. Arnbjerg, “Complex vertebral malformation in Holstein calves,” Journal of Veterinary Diagnostic Investigation, vol. 13, no. 4, pp. 283–289, 2001. View at: Publisher Site | Google Scholar
  34. P. M. VanRaden, K. M. Olson, D. J. Null, and J. L. Hutchison, “Harmful recessive effects on fertility detected by absence of homozygous haplotypes,” Journal of Dairy Science, vol. 94, no. 12, pp. 6153–6161, 2011. View at: Publisher Site | Google Scholar
  35. C. Charlier, J. S. Agerholm, W. Coppieters et al., “A deletion in the bovine FANCI gene compromises fertility by causing fetal death and brachyspina,” PLoS ONE, vol. 7, no. 8, Article ID e43085, 2012. View at: Publisher Site | Google Scholar
  36. I. Hoffmann, “Climate change and the characterization, breeding and conservation of animal genetic resources,” Animal Genetics, vol. 41, no. 1, pp. 32–46, 2010. View at: Publisher Site | Google Scholar
  37. L. K. Matukumalli, C. T. Lawley, R. D. Schnabel et al., “Development and characterization of a high density SNP genotyping assay for cattle,” PLoS ONE, vol. 4, no. 4, Article ID e5350, 2009. View at: Publisher Site | Google Scholar


Copyright © 2016 Laura Iacolina et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Materials and Methods

At-Risk Dog Dataset

We queried Embark’s customer database on April 4 th , 2018 for all dogs whose owners consented to participate in research that were homozygous (at-risk) for recessive deleterious conditions assayed by Embark’s platform. In total, we identified 678 at-risk cases in 670 dogs (some dogs were at-risk for more than one condition). We separated these at-risk cases into two categories: 1) at-risk for SOD1-based degenerative myelopathy (Awano et al. 2009), of which we observed 283 at-risk dogs, and 2) at-risk for all 28 other recessive deleterious conditions assayed by Embark, of which we observed 395 at-risk cases across 393 dogs (Tables S1, S2).

Breed Dog Dataset

We queried Embark’s customer database on January 23 rd , 2018 for all customer dogs identified as purebred by Embark from the most common 11 breeds and whose owners consented to participate in research. We then used the ‘–genome’ flag in PLINK v1.9 (Chang et al. 2015) to identify pairs of dogs for which the proportion of IBD (PI_HAT) was greater than 0.45 and used these pairs to remove dogs that were potentially related as parent-offspring or full siblings. In total, our final dataset included 1,792 dogs from 11 breeds (Table S3).

Genotyping & Quality Control

Customer dogs were genotyped on Embark’s custom high-density genotyping platform containing approximately 220,000 markers including all 173,000 markers found on the Illumina CanineHD platform and probes to detect over 160 Mendelian disease variants. SNP filtering using PLINK 1.9 (Chang et al. 2015) was done to ensure genotype concordance rates above 99.99% and missingness rates below 0.1%. Genotype data were phased against a proprietary reference panel and missing data imputed using Eagle2 (Loh et al. 2016). SNP data were also pruned with PLINK to remove markers in close linkage disequilibrium using “–indep-pairwise 200 100 0.90”. After pruning, 170,728 autosomal and 4,395 chrX markers remained, for an average of one marker per 12.8 kb for autosomes (one marker per 28.2 kb on chromosome X).

Defining Runs of Homozygosity with PLINK

We generated ROH for at-risk dogs in PLINK using software version 1.9 (Chang et al. 2015) (which uses the algorithm from software version 1.07 (Purcell et al. 2007)).

Watch the video: Runs of Homozygosity, Consanguinity, and Jewish Populations - Noah Rosenberg (December 2022).