These tools also help prevent the disorders caused by recessive genes. The more genes two animals share, the less productive their progeny will be. Scientists recommend that a sire and dam should share no more than 6. Inbreeding also increases the risk of disorders caused by recessive genes. These disorders can lead to calf abnormalities, miscarriages and stillbirths. Animals must have two copies of a recessive gene to have the disorder. They receive one copy of the gene from each parent.
Animals that are closely related are more likely to carry a copy of the same recessive gene. This increases the risk they will both pass a copy of the gene onto their offspring. We have several tools available to prevent matings between animals that carry the same recessive gene. Our DataMATE app makes it easy for our artificial breeding technicians to calculate the risk of a particular mating.
DataMATE issues a warning if the animals are likely to share more than 6. The technician can then inseminate the cow with a more suitable bull. If one of the genes in the pair is dominant, then the result is you gain the trait of the dominant gene. However, for traits that originate from the recessive gene, you need both genes to be recessive.
For example, the gene for brown eyes is dominant and so having just one of these in a pair will result in your eyes being brown. This is important as certain congenital defects and genetic diseases, such as cystic fibrosis, are carried by recessive alleles. Inbreeding stacks the odds of being born with such conditions against you. As blood-relative mating partners have similar DNA, the changes of them carrying the same recessive gene is greatly increased. According to a study , the rate of near natal and childhood death increases if the child comes from a first cousin union, nearly doubling in certain countries.
As inbreeding comes with such a high cost, the logic of engaging it might seem baffling. In hereditary systems of rule, such as the pharaohs of Ancient Egypt, inbreeding prevented another family marrying in and lining up to take the throne.
A study examined adult Egyptian mummies and found that royal mummies had consistently different heights from the general population, with male royals being taller than average and female royals being shorter than average.
A more recent example is the House of Habsburg, whose empire included Spain, Austria and Hungary; the family line ending with Charles II of Spain, who was born in Charles suffered from numerous disabilities and congenital defects. His autopsy report is a staggering read. It states that after his death Charles had no blood, a heart the size of a peppercorn, corroded lungs, a head full of water, rotten and gangrenous intestines and had only a single testicle that was as black as coal.
While not all of these can be blamed on inbreeding pituitary hormone deficiency and distal renal tubular acidosis could explain several of these conditions both are caused by recessive alleles.
The main objective of this study was to evaluate the hypothesis that recent inbreeding is more harmful than ancient inbreeding. This hypothesis was based on the expected decrease in frequency of deleterious alleles over time as a result of selection, strengthened by purging. Computer simulations have shown that purging is more effective when selection pressure is strong and when inbreeding accumulates slowly over many generations [ 9 , 19 ]. We expected that purging would have occurred in the Dutch Holstein—Friesian population, because the population has undergone decades of intense artificial selection and inbreeding has accumulated at least until at approximately 0.
Pedigree-based results support our hypothesis. For yield traits, inbreeding on recent generations was more harmful than inbreeding on more distant generations Fig. In addition, there was evidence of purging for these traits Fig. In other words, to be IBD for alleles that were already IBD in the past had a neutral or favourable effect, whereas to be IBD for alleles for the first time was generally unfavourable.
These findings are in line with the hypothesis of purging, which states that loci that have undergone inbreeding in the past have been exposed to an increased selection efficiency against deleterious recessive alleles , compared to loci that have not undergone inbreeding before. Our results are largely in line with previous studies that have investigated purging in commercial cattle populations [ 4 , 23 ].
In German Holstein—Friesian cattle, Hinrichs et al. For calving interval, they estimated an increase of 4. In this study and in the study of Hinrichs et al. In the study of Mc Parland et al. Differences between effects of recent and ancient inbreeding Fig. This finding may be explained by the selection history of Dutch Holstein—Friesian cattle. Targeted selection for fertility and udder health has taken place only since these traits were included in the breeding goal around the year , whereas selection for yield traits has taken place for many more decades [ 42 ].
Therefore, there has been less time for selection to act on alleles that affect fertility and udder health traits compared to alleles that affect yield traits.
The rationale behind this recently introduced measure is that purging is not fully efficient and that the probability of purging increases with the number of times the alleles have been IBD. Indeed, we observed a few favourable effects, i. Most traits showed no significant effect, but the estimate was generally favourable.
In Thoroughbred horses, Todd et al. This can be explained by the very comprehensive pedigree of the Thoroughbred population, which dates back to the late eighteenth century, with individuals from to having a mean CGE of More recently, an inbreeding-purging IP model was proposed to assess purging based on genealogical information [ 52 ].
We considered using the IP model for the current study. Since the model and associated software PURGd have been developed outside the context of artificially selected populations, various limitations exist for its application to livestock data.
First, random effects cannot be fitted in the model, making it impossible to directly correct for additive genetic relationships. To overcome this limitation, one could first run an animal model in a different software environment e. ASReml and subsequently use the residuals as phenotypes for the IP model. This two-step process is not desirable, because it will affect the inbreeding depression estimates.
Second, the model assumes that inbreeding load is due to deleterious alleles that have a low initial frequency in the base population. In the context of livestock breeding, where animals are selected based on a breeding goal composed of various traits [ 42 ], we do not expect that alleles that are deleterious for a single trait necessarily segregate at a low frequency.
Given these limitations, we decided not to use the IP model in the current study. For future research, it would be valuable to explore further the application of the IP model in livestock populations undergoing artificial selection. We expected that inbreeding based on long ROH recent inbreeding would be associated with stronger depression effects than inbreeding based on short ROH ancient inbreeding.
Overall, both long and short ROH seemed to contribute to inbreeding depression. Only a few studies have investigated the effect of ROH of different lengths on phenotypes in livestock populations, with various results [ 1 , 18 , 26 ]. For autosome 3 in Iberian pigs, Saura et al. To further investigate and compare our results to the findings of Pryce et al.
We obtained a similar trend see Additional file 4 : Figure S3 as Pryce et al. The difference between results for fitting multiple length classes simultaneously Fig. We believe that fitting length classes simultaneously provides the most accurate estimates, since this approach accounts for the correlations between classes.
Based on computer simulations, Keller et al. Functional predictions of deleterious variation have led to inconsistent conclusions as to whether short or long ROH harbour more deleterious genetic variants [ 54 , 55 ]. For the human genome, Szpiech et al. In contrast, for four Danish cattle breeds Zhang et al. For domestic dogs, Sams and Boyko [ 56 ] recently reported that the relative risk of a ROH carrying a known deleterious variant is similar across ROH of different lengths, suggesting that ROH of all lengths may contribute to inbreeding depression in dogs.
This latter finding is more in line with our results, where both short and long ROH seem to contribute to inbreeding depression. There are various aspects that affect the accuracy of identification of ROH and the inference of inbreeding age based on ROH. Previous studies have shown that the use of a 50 k panel may result in false positive ROH shorter than 5 Mb and especially in many false positives ROH shorter than 2 Mb [ 57 , 58 ].
For a more accurate estimation of ancient inbreeding, and to apply this approach to even more generations in the past, high-density SNP data or sequence data is required.
Second, in this study we assumed a uniform recombination rate, while it actually varies across the genome e. A ROH of a given physical length in a region with high recombination will reflect more ancient inbreeding than a ROH of the same length in a region with low recombination.
One may account for this effect by computing ROH based on genetic distances. However, this is rarely done in practice, since it requires a high-quality linkage map [ 59 ].
Third, recent inbreeding may mask more ancient inbreeding [ 26 ]. If both chromosomes at a position in the genome trace back to a distant common ancestor, you expect to find a short ROH. If the same region also traces back to a recent common ancestor, then you would observe only the long ROH. As a result, one may expect a negative correlation between recent and ancient ROH-based inbreeding.
In Iberian pigs, Saura et al. However, these negative correlations could also be an artefact of the unreliable estimation of short ROH.
The effect of this or other correction s should be investigated in future studies. Lastly, various approaches can be used to identify ROH. In this study, we applied the sliding window approach implemented in Plink 2. In the future, it would be valuable to compare the different approaches and investigate the benefit of using linkage maps to infer inbreeding age based on ROH.
As sequencing costs continue to decrease, genomic data including that of cows will become increasingly available. This offers opportunities to perform large-scale analyses on genomic inbreeding depression based on high-density information, e. In addition, genomic time series consisting of genomic data of an individual and its ancestors could be used to study purging in more detail at the genomic level. Inbreeding depression was observed for yield, fertility and udder health traits in Dutch Holstein—Friesian dairy cattle.
Observed inbreeding depression was stronger for yield traits than for fertility and udder health traits, when compared in phenotypic or genetic standard deviations. Genomic inbreeding captured more inbreeding depression than pedigree-based inbreeding at the population level.
For yield traits and based on pedigree information, inbreeding on recent generations was found to be more harmful than inbreeding on distant generations and there was evidence of purging. Future work should investigate inbreeding depression and purging in more detail at the genomic level, using higher density information and genomic time series.
All information supporting the results is included in the text, figures and tables of this article. The dataset is not publicly available due to commercial restrictions.
Identification of genomic regions associated with inbreeding depression in Holstein and Jersey dairy cattle. Genet Sel Evol. Article Google Scholar. Evaluation of inbreeding depression in Holstein cattle using whole-genome SNP markers and alternative measures of genomic inbreeding. J Dairy Sci. Estimation of intrachromosomal inbreeding depression on female fertility using runs of homozygosity in Finnish Ayrshire cattle.
Purging of inbreeding depression within the Irish Holstein—Friesian population. Leroy G. Inbreeding depression in livestock species: review and meta-analysis. Anim Genet. Invited review: Inbreeding in the genomics era: Inbreeding, inbreeding depression, and management of genomic variability.
Charlesworth B, Charlesworth D. The genetic basis of inbreeding depression. Genet Res. Charlesworth D, Willis JH.
The genetics of inbreeding depression. Nat Rev Genet. Understanding inbreeding depression, purging, and genetic rescue. Trends Ecol Evol. The effects of inbreeding on the lifetime performance of dairy cattle. Production traits of Holstein cattle: estimation of nonadditive genetic variance components and inbreeding depression.
Inbreeding depression for global and partial economic indexes, production, type, and functional traits. Runs of homozygosity in European populations. Am J Hum Genet. VanRaden PM. Efficient methods to compute genomic predictions. Variation in actual relationship as a consequence of Mendelian sampling and linkage.
Oliehoek PA, Bijma P. Effects of pedigree errors on the efficiency of conservation decisions. Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data. Genome-wide mapping and estimation of inbreeding depression of semen quality traits in a cattle population. Boakes E, Wang J. A simulation study on detecting purging of inbreeding depression in captive populations. Measuring inbreeding and inbreeding depression on pig growth from pedigree or SNP-derived metrics.
J Anim Breed Genet. PubMed Google Scholar. Conserv Biol. GRAIN: a computer program to calculate ancestral and partial inbreeding coefficients using a gene dropping approach. Estimation of ancestral inbreeding effects on stillbirth, calving ease and birthweight in German Holstein dairy cattle.
Speed D, Balding DJ. Relatedness in the post-genomic era: is it still useful? Browning SR. Estimation of pairwise identity by descent from dense genetic marker data in a population sample of haplotypes.
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