J.J. Windig

Estimating Relatedness Between Individuals in General Populations With a Focus on Their Use in Conservation Programs

Relatedness estimators are widely used in genetic studies, but effects of population structure on performance of estimators, criteria to evaluate estimators, and benefits of using such estimators in conservation programs have to date received little attention. In this article we present new estimators, based on the relationship between coancestry and molecular similarity between individuals, and compare them with existing estimators using Monte Carlo simulation of populations, either panmictic or structured. Estimators were evaluated using statistical criteria and a diversity criterion that minimized relatedness. Results show that ranking of estimators depends on the population structure. An existing estimator based on two-gene and four-gene coefficients of identity performs best in panmictic populations, whereas a new estimator based on coancestry performs best in structured populations. The number of marker alleles and loci did not affect ranking of estimators. Statistical criteria were insufficient to evaluate estimators for their use in conservation programs. The regression coefficient of pedigree relatedness on estimated relatedness (β2) was substantially lower than unity for all estimators, causing overestimation of the diversity conserved. A simple correction to achieve β2 = 1 improves both existing and new estimators. Using relatedness estimates with correction considerably increased diversity in structured populations, but did not do so or even decreased diversity in panmictic populations.

Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection.

Mitigation of enteric methane (CH₄) emission in ruminants has become an important area of research because accumulation of CH₄ is linked to global warming. Nutritional and microbial opportunities to reduce CH₄ emissions have been extensively researched, but little is known about using natural variation to breed animals with lower CH₄ yield. Measuring CH₄ emission rates directly from animals is difficult and hinders direct selection on reduced CH₄ emission. However, improvements can be made through selection on associated traits (e.g., residual feed intake, RFI) or through selection on CH₄ predicted from feed intake and diet composition. The objective was to establish phenotypic and genetic variation in predicted CH₄ output, and to determine the potential of genetics to reduce methane emissions in dairy cattle. Experimental data were used and records on daily feed intake, weekly body weights, and weekly milk production were available from 548 heifers. Residual feed intake (MJ/d) is the difference between net energy intake and calculated net energy requirements for maintenance as a function of body weight and for fat- and protein-corrected milk production. Predicted methane emission (PME; g/d) is 6% of gross energy intake (Intergovernmental Panel on Climate Change methodology) corrected for energy content of methane (55.65 kJ/g). The estimated heritabilities for PME and RFI were 0.35 and 0.40, respectively. The positive genetic correlation between RFI and PME indicated that cows with lower RFI have lower PME (estimates ranging from 0.18 to 0.84). Hence, it is possible to decrease the methane production of a cow by selecting more-efficient cows, and the genetic variation suggests that reductions in the order of 11 to 26% in 10 yr are theoretically possible, and could be even higher in a genomic selection program. However, several uncertainties are discussed; for example, the lack of true methane measurements (and the key assumption that methane produced per unit feed is not affected by RFI level), as well as the limitations of predicting the biological consequences of selection. To overcome these limitations, an international effort is required to bring together data on feed intake and methane emissions of dairy cows.

Alternative Somatic Cell Count Traits as Mastitis Indicators for Genetic Selection

The aim of this study was to define alternative traits of somatic cell count (SCC) that can be used to decrease genetic susceptibility to clinical and subclinical mastitis (CM and SCM, respectively). Three kinds of SCC traits were evaluated: 1) lactation-averages of SCC, 2) traits derived from the proportion of test-day SCC above 150,000 cells/mL, and 3) patterns of peaks in SCC. Genetic parameters for these SCC traits and their genetic correlation with CM and SCM were estimated; CM and SCM were scored as binary traits. Two data sets (A and B) depending on CM recording were available. After editing, subset A contained 28,688 lactations from 21,673 cows in 394 herds. Subset B contained 56,726 lactations of 30,145 cows in 272 herds. Variance components for sire and permanent animal effects were estimated. Estimated heritabilities for all mastitis traits were around 0.03. Heritabilities for SCC traits ranged from 0.01 for patterns of peaks in SCC to 0.13 for lactation-average SCC. Genetic correlations between SCC traits and CM or SCM ranged from 0.55 to 0.93 for CM and from 0.55 to 0.98 for SCM. High genetic correlations were estimated between CM and SCC averaged over 250 d in milk (0.87), and between SCM and presence of test-day SCC >150,000 cells/mL (0.98) in subset A. In subset B, a high genetic correlation was estimated between CM and an SCC peak with a quick recovery (0.93) and between SCM and SCC averaged between 151 and 400 d (0.95). Partial genetic correlations were calculated to investigate the additional information of the alternative SCC traits, compared with lactation-average SCC. They showed that some traits remain informative for CM and others for SCM. Therefore, use of information from a combination of different SCC traits may be more successful in improving overall udder health than the traditional single SCC measure.

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values.

The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction.

Combining somatic cell count traits for optimal selection against mastitis

Test-day records of somatic cell counts (SCC) can be used to define alternative traits to decrease genetic susceptibility to clinical mastitis (CM) and subclinical mastitis (SCM). This paper examines which combination of alternative SCC traits can be used best to reduce both CM and SCM and whether direct information on CM is useful in this respect. Genetic correlations between 10 SCC traits and CM and SCM were estimated from 3 independent data sets. The SCC traits with the strongest correlations with CM differed from those with the strongest correlations with SCM. Selection index calculations were made for a breeding goal of 50% CM and 50% SCM resistance using these correlations. They indicated that a combination of 5 SCC traits (SCC early and late in lactation, suspicion of infection based on increased SCC, extent of increased SCC, and presence of a peak pattern in SCC) gave a high accuracy, almost without loss, compared with the full set of 10 SCC traits. The estimated accuracy of this index was 0.91, assuming that the correlations had been estimated without error. To take errors in estimation into account, correlations were resampled from a normal distribution with mean and standard errors as originally estimated. The accuracy of the index calculated with the original correlations was then recalculated using the resampled correlations. The average accuracy based on 50,000 resamplings decreased to 0.81. Use of direct information on CM improved the accuracy (uncorrected for errors in correlations) only slightly, to 0.92.

Eradication of scrapie with selective breeding: are we nearly there?

BackgroundFollowing EU decision 2003/100/EC Member States have recently implemented sheep breeding programmes to reduce the prevalence of sheep with TSE susceptible prion genotypes. The present paper investigates the progress of the breeding programme in the Netherlands. The PrP genotype frequencies were monitored through time using two sets of random samples: one set covers the years 2005 to 2008 and is taken from national surveillance programme; the other is taken from 168 random sheep farms in 2007. The data reveal that although the level of compliance to the breeding programme has been high, the frequency of susceptible genotypes varies substantially between farms. The 168 sheep farms are a subset of 689 farms participating in a postal survey inquiring about management and breeding strategies. This survey aimed to identify how much these strategies varied between farms, in order to inform assessment of the expected future progress towards eradication of classical scrapie.ResultsOn the one hand, we found that compliance to the national breeding program has been high, and the frequency of resistant genotypes is expected to increase further in the next few years. On the other hand, we observed a large variation in prevalence of the scrapie resistant PrP genotype ARR between farms, implicating a large variation of genetic resistance between farms. Substantial between-flock differences in management and breeding strategies were found in the postal survey, suggesting considerable variation in risk of scrapie transmission between farms.ConclusionsOur results show that although there has been a good progress in the breeding for scrapie resistance and the average farm-level scrapie susceptibility in the Netherlands has been significantly reduced, still a considerable proportion of farms contain high frequencies of susceptible genotypes in their sheep population. Since 2007 the breeding for genetic resistance is voluntarily again, and participation to selective breeding can decrease as a result of this. This, together with the patterns of direct and indirect contact between sheep farms, might present a challenge of the aim of scrapie eradication. Communication to sheep owners of the effect of the breeding programme thus far, and of the prospects for classical scrapie eradication in The Netherlands might be essential for obtaining useful levels of participation to the voluntary continuation of the breeding programme.

Consequences for diversity when prioritizing animals for conservation with pedigree or genomic information

Up to now, prioritization of animals for conservation has been mainly based on pedigree information; however, genomic information may improve prioritization. In this study, we used two Holstein populations to investigate the consequences for genetic diversity when animals are prioritized with optimal contributions based on pedigree or genomic data and whether consequences are different at the chromosomal level. Selection with genomic kinships resulted in a higher conserved diversity, but differences were small. Largest differences were found when few animals were prioritized and when pedigree errors were present. We found more differences at the chromosomal level, where selection based on genomic kinships resulted in a higher conserved diversity for most chromosomes, but for some chromosomes, pedigree-based selection resulted in a higher conserved diversity. To optimize conservation strategies, genomic information can help to improve the selection of animals for conservation in those situations where pedigree information is unreliable or absent or when we want to conserve diversity at specific genome regions.

Characterization of distributions of somatic cell counts.

There is more useful information in distributions of somatic cell count (SCC) than is currently used in practice. Analysis of SCC of individual quarters (n = 450,834 quarter records of 133,102 cows) showed that the presence of pathogens did not change the peak of the SCC distribution. Instead, the percentages of observations in the tail changed. Probability density functions of specified sets of up to 5 standard distributions were then fitted on the number of records per class, using a maximum likelihood procedure. Analysis of cow SCC (2 data sets: n = 335,135 test-day records of 41,567 cows on 407 farms and n = 1,665,431 test-day records) showed that a mixture of a normal, a log-normal and an exponential density function (N+LN+E) best described the distribution of SCC. A mixture of 4 normal and an exponential distribution (4N+E) was also a good approximation. For this last mixture, each distribution could be associated with presence or absence of pathogens. The first 2 normal distributions appear to consist of uninfected cows and cows recovering from an infection, the third normal distribution may be associated with minor pathogens, and the fourth normal and the exponential distribution with major pathogens and persistent infections. Estimated percentages of records in each underlying distribution differed between parities, between stages of lactation, and between records with previous records being above or below 100,000 cells/mL. The categorical nature of cow-SCC can be utilized by deriving new traits such as the fraction of cow-SCC records in a lactation that are associated with an infection with a major pathogen.

Conservation priorities for Ethiopian sheep breeds combining threat status, breed merits and contributions to genetic diversity

Prioritizing livestock breeds for conservation needs to incorporate both genetic and non-genetic aspects important for the survival of the breeds. Here, we apply a maximum-utility-strategy to prioritize 14 traditional Ethiopian sheep breeds based on their threat status, contributions to farmer livelihoods (current breed merits) and contributions to genetic diversity. Contributions of the breeds to genetic diversity were quantified using Edings marker-estimated kinship approaches. Non-genetic aspects included threats (e.g. low population size, low preferences by farmers) and current merits (economic, ecological and cultural merits). Threat analysis identified eight of the 14 breeds as threatened. Analysis of current merits showed that sub-alpine and arid-lowland breeds contribute most to farmer livelihoods in comparison to other breeds. The highest contribution to the genetic diversity conserved was from the Simien breed. Simien showed high between-breed (low between-breed kinship = 0.04) as well as high within-breed diversity (low within-breed kinship = 0.09 and high HE = 0.73 and allelic richness = 6.83). We combined the results on threat status, current breed merits and contributions to genetic diversity to produce a ranking of the 14 breeds for conservation purposes. Our results balance the trade-offs between conserving breeds as insurance against future uncertainties and current sustainable utilization. The ranking of breeds provides a basis for conservation strategies for Ethiopian sheep and contributes to a regional or global conservation plan.

Genetic parameters for androstenone, skatole, indole, and human nose scores as measures of boar taint and their relationship with finishing traits

The purpose of this study was to evaluate measures of boar (Sus scrofa) taint as potential selection criteria to reduce boar taint so that castration of piglets will become unnecessary. Therefore, genetic parameters of boar taint measures and their genetic correlations with finishing traits were estimated. In particular, the usefulness of a human panel assessing boar taint (human nose score) was compared with chemical assessment of boar taint compounds, androstenone, skatole, and indole. Heritability estimates for androstenone, skatole, and indole were 0.54, 0.41, and 0.33, respectively. The heritability for the human nose score using multiple panelists was 0.12, and ranged from 0.12 to 0.19 for individual panelists. Genetic correlations between scores of panelists were generally high up to unity. The genetic correlations between human nose scores and the boar taint compounds ranged from 0.64 to 0.999. The boar taint compounds and human nose scores had low or favorable genetic correlations with finishing traits. Selection index estimates indicated that the effectiveness of a breeding program based on human nose scores can be comparable to a breeding program based on the boar taint compounds themselves. Human nose scores can thus be used as a cheap and fast alternative for the costly determination of boar taint compounds, needed in breeding pigs without boar taint.