Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein-Friesian breeding program from 1986 to 2015

Effect of germplasm exchange strategies on genetic gain, homozygosity, and genetic diversity in dairy stud populations: A simulation study

While genomic selection has led to considerable improvements in genetic gain, it has also seemingly led to increased rates of inbreeding and homozygosity, which can negatively affect genetic diversity and the long-term sustainability of dairy populations. Using genotypes from US Holstein animals from 3 distinct stud populations, we performed a simulation study consisting of 10 rounds of selection, with each breeding population composed of 200 males and 2000 females. The investigated selection strategies consisted of selection using true breeding values (TBV), estimated breeding values (EBV), estimated breeding values penalized for the average future genomic inbreeding of progeny (PEN-EBV), or random selection (RAND). We also simulated several germplasm exchange strategies where the germplasm of males from other populations was used for breeding. These strategies included exchanging males based on EBV, PEN-EBV, low genomic future inbreeding of progeny (GFI), or randomly (RAND). Variations of several parameters, such as the correlation between the selection objectives of populations and the size of the exchange, were simulated. Penalizing genetic merit to minimize genomic inbreeding of progeny provided similar genetic gain and reduced the average homozygosity of populations compared with the EBV strategy. Germplasm exchange was found to generally provide long-term benefits to all stud populations. In both the short and long-term, germplasm exchange using the EBV or PEN-EBV strategies provided more cumulative genetic progress than the no-exchange strategy; the amount of long-term genetic progress achieved with germplasm exchange using these strategies was higher for scenarios with a higher genetic correlation between the traits selected by the studs and for a larger size of the exchange. Both the PEN-EBV and GFI exchange strategies allowed decreases in homozygosity and provided significant benefits to genetic diversity compared with other strategies, including larger average minor allele frequencies and smaller proportions of markers near fixation. Overall, this study showed the value of breeding strategies to balance genetic progress and genetic diversity and the benefits of cooperation between studs to ensure the sustainability of their respective breeding programs.

Analyzing Runs of Homozygosity Reveals Patterns of Selection in German Brown Cattle

An increasing trend in ancestral and classical inbreeding coefficients as well as inbreeding depression for longevity were found in the German Brown population. In addition, the proportion of US Brown Swiss genes is steadily increasing in German Browns. Therefore, the aim of the present study was to analyze the presence and genomic localization of runs of homozygosity (ROH) in order to evaluate their associations with the proportion of US Brown Swiss genes and survival rates of cows to higher lactations. Genotype data were sampled in 2364 German Browns from 258 herds. The final data set included 49,693 autosomal SNPs. We identified on average 35.996 ± 7.498 ROH per individual with a mean length of 8.323 ± 1.181 Mb. The genomic inbreeding coefficient FROH was 0.122 ± 0.032 and it decreased to 0.074, 0.031 and 0.006, when genomic homozygous segments > 8 Mb (FROH>8), >16 Mb (FROH>16) and >32 Mb (FROH>32) were considered. New inbreeding showed the highest correlation with FROH>32, whereas ancestral inbreeding coefficients had the lowest correlations with FROH>32. The correlation between the classical inbreeding coefficient and FROH was 0.572. We found significantly lower FROH, FROH>4, FROH>8 and FIS for US Brown Swiss proportions <60% compared to >80%. Cows surviving to the 2nd, 4th, 6th, 8th, and 10th lactation had lower genomic inbreeding for FROH and up to FROH>32, which was due to a lower number of ROH and a shorter average length of ROH. The strongest ROH island and consensus ROH shared by 50% of the animals was found on BTA 6 at 85-88 Mb. The genes located in this genomic region were associated with longevity (NPFFR2 and ADAMTS3), udder health and morphology (SLC4A4, NPFFR2, GC and RASSF6), milk production, milk protein percentage, coagulation properties of milk and milking speed (CSN3). On BTA 2, a ROH island was detected only in animals with <60% US Brown Swiss genes. Genes within this region are predominantly important for dual-purpose cattle breeds including Original Browns. For cows reaching more than 9 lactations, an exclusive ROH island was identified on BTA 7 with genes assumed to be associated with longevity. The analysis indicated that genomic homozygous regions important for Original Browns are still present and also ROH containing genes affecting longevity may have been identified. The breeding of German Browns should prevent any further increase in genomic inbreeding and run a breeding program with balanced weights on production, robustness and longevity.

Genomic analysis of inbreeding and coancestry in Nordic Jersey and Holstein dairy cattle populations

In recent years, genomic selection (GS) has accelerated genetic gain in dairy cattle breeds worldwide. Despite the evident genetic progress, several dairy populations have also encountered challenges such as heightened inbreeding rates and reduced effective population sizes. The challenge has been to find a balance between achieving substantial genetic gain while managing genetic diversity within the population, thereby mitigating the negative effects of inbreeding depression. This study aims to elucidate the impact of GS on pedigree and genomic rates of inbreeding (ΔF) and coancestry (ΔC) in Nordic Jersey (NJ) and Holstein (NH) cattle populations. Furthermore, key genetic metrics, including the generation interval (L), effective population size (Ne), and future effective population size (FNe) were assessed between 2 time periods, before and after GS, and across distinct animal cohorts in both breeds: females, bulls, and approved semen-producing bulls (AI-sires). Analysis of ΔF and ΔC revealed distinct trends across the studied periods and animal groups. Notably, there was a consistent increase in yearly ΔF for most animal groups in both breeds. An exception was observed in NH AI-sires, which demonstrated a slight decrease in yearly ΔF. Moreover, NJ displayed minimal changes in yearly ΔC between the periods, whereas NH exhibited elevated ΔC values across all animal groups. Particularly striking was the substantial increase in yearly ΔC within the NH female population, surging from 0.02% to 0.39% between the periods. Implementation of GS resulted in a reduction of the generation interval across all animal cohorts in both NJ and NH breeds. However, the extent of reduction was more pronounced in males compared with females. This reduction in generation interval influenced generational changes in ΔF and ΔC. Bulls and AI-sires of both breeds exhibited reduced generational ΔF between periods, in contrast to females that demonstrated an opposing pattern. Between the periods, NJ maintained a relatively stable Ne (29.4 before and 30.3 after GS), whereas NH experienced a notable decline from 54.3 to 42.8. Female groups in both breeds displayed a negative Ne trend, whereas males demonstrated either neutral or positive Ne developments. Regarding FNe, NJ exhibited positive FNe development with an increase from 40.7 to 57.2. The opposite was observed in NH, where FNe decreased from 198.8 to 42.7. In summary, it was evident that the genomic methods could detect differences between the populations and changes in ΔF and ΔC more efficiently than pedigree methods. Implementation of GS yielded positive outcomes within the NJ population regarding the rate of coancestry but the opposite was observed with NH. Moreover, analysis of ΔC data hints at the potential to decrease future ΔF through informed mating strategies. Conversely, NH faces more pressing concerns, even though ΔF remains comparatively modest in contrast to what has been observed in other Holstein populations. These findings underscore the necessity of genomic control of inbreeding and coancestry with strategic changes in the Nordic breeding schemes for dairy to ensure long-term sustainability in the forthcoming years.

Assessing different metrics of pedigree and genomic inbreeding and inbreeding effect on growth, fertility, and feed efficiency traits in a closed-herd Nellore cattle population

BACKGROUND

The selection of individuals based on their predicted breeding values and mating of related individuals can increase the proportion of identical-by-descent alleles. In this context, the objectives of this study were to estimate inbreeding coefficients based on alternative metrics and data sources such as pedigree (FPED), hybrid genomic relationship matrix H (FH), and ROH of different length (FROH); and calculate Pearson correlations between the different metrics in a closed Nellore cattle population selected for body weight adjusted to 378 days of age (W378). In addition to total FROH (all classes) coefficients were also estimated based on the size class of the ROH segments: FROH1 (1-2 Mb), FROH2 (2-4 Mb), FROH3 (4-8 Mb), FROH4 (8-16 Mb), and FROH5 (> 16 Mb), and for each chromosome (FROH_CHR). Furthermore, we assessed the effect of each inbreeding metric on birth weight (BW), body weights adjusted to 210 (W210) and W378, scrotal circumference (SC), and residual feed intake (RFI). We also evaluated the chromosome-specific effects of inbreeding on growth traits.

RESULTS

The correlation between FPED and FROH was 0.60 while between FH and FROH and FH and FPED were 0.69 and 0.61, respectively. The annual rate of inbreeding was 0.16% for FPED, 0.02% for FH, and 0.16% for FROH. A 1% increase in FROH5 resulted in a reduction of up to -1.327 ± 0.495 kg in W210 and W378. Four inbreeding coefficients (FPED, FH, FROH2, and FROH5) had a significant effect on W378, with reductions of up to -3.810 ± 1.753 kg per 1% increase in FROH2. There was an unfavorable effect of FPED on RFI (0.01 ± 0.0002 kg dry matter/day) and of FROH on SC (-0.056 ± 0.022 cm). The FROH_CHR coefficients calculated for BTA3, BTA5, and BTA8 significantly affected the growth traits.

CONCLUSIONS

Inbreeding depression was observed for all traits evaluated. However, these effects were greater for the criterion used for selection of the animals (i.e., W378). The increase in the genomic inbreeding was associated with a higher inbreeding depression on the traits evaluated when compared to pedigree-based inbreeding. Genomic information should be used as a tool during mating to optimize control of inbreeding and, consequently, minimize inbreeding depression in Nellore cattle.

Genomic analysis of conservation status, population structure and admixture in local Czech and Slovak dairy goat breeds

While dairy goat production, characterized by traditional production on small farms, is an important source of income in the Czech Republic and Slovakia, locally adapted breeds have not been fully consolidated over the last 100 years due to large fluctuations in population size and inconsistent breeding programs that allowed for different crossbreeding strategies. Our main objective in this study was therefore to assess the conservation status of 4 Czech (Alpine Goat, White Shorthair, Brown Shorthair and Czech Landrace) and one Slovak (Slovak White Shorthair) local goat breeds, to analyze their population structure and admixture, and to estimate their relatedness to several neighboring breeds. Our analyses included 142 goats belonging to 5 local breeds genotyped with the Illumina 50K BeadChip and 618 previously genotyped animals representing 15 goat breeds from Austria and Switzerland (all analyses based on 46,862 autosomal SNPs and 760 animals). In general, the conservation status of the Czech and Slovak local goat breeds was satisfactory, with the exception of the Brown Shorthair goat, as the analyzed parameters (heterozygosity, haplotype richness, ROH-based inbreeding and effective population size) were mostly above the median of 20 breeds. However, for all 5 Czech and Slovakian breeds, an examination of historical effective population size indicated a substantial decline about 8 to 22 generations ago. In addition, our study revealed that the Czech and Slovakian breeds are not fully consolidated; for instance, White Shorthair and Brown Shorthair were not clearly distinguishable. Considerable admixture, especially in Czech Landrace (effective number of parental clusters equal to 4.2), and low but numerous migration rates from other Austrian and Swiss breeds were found. These results provide valuable insights for future breeding programs and genetic diversity management of local Czech and Slovak goat breeds.

Inbreeding depression for producer-recorded udder, metabolic, and reproductive diseases in US dairy cattle

This study leveraged a growing dataset of producer-recorded phenotypes for mastitis, reproductive diseases (metritis and retained placenta), and metabolic diseases (ketosis, milk fever, and displaced abomasum) to investigate the potential presence of inbreeding depression for these disease traits. Phenotypic, pedigree, and genomic information were obtained for 354,043 and 68,292 US Holstein and Jersey cows, respectively. Total inbreeding coefficients were calculated using both pedigree and genomic information; the latter included inbreeding estimates obtained using a genomic relationship matrix and runs of homozygosity. We also generated inbreeding coefficients based on the generational inbreeding for recent and old pedigree inbreeding, for different run-of-homozygosity length classes, and for recent and old homozygous-by-descent segment-based inbreeding. Estimates on the liability scale revealed significant evidence of inbreeding depression for reproductive-disease traits, with an increase in total pedigree and genomic inbreeding showing a notable effect for recent inbreeding. However, we found inconsistent evidence for inbreeding depression for mastitis or any metabolic diseases. Notably, in Holsteins, the probability of developing displaced abomasum decreased with inbreeding, particularly for older inbreeding. Estimates of disease probability for cows with low, average, and high inbreeding levels did not significantly differ across any inbreeding coefficient and trait combination, indicating that although inbreeding may affect disease incidence, it likely plays a smaller role compared with management and environmental factors.

Genetic Variation and Composition of Two Commercial Estonian Dairy Cattle Breeds Assessed by SNP Data

The aims of this study were to assess the genomic relatedness of Estonian and selected European dairy cattle breeds and to examine the within-breed diversity of two Estonian dairy breeds using genome-wide SNP data. This study was based on a genotyped heifer population of the Estonian Red (ER) and Estonian Holstein (EH) breeds, including about 10% of all female cattle born in 2017-2020 (sample sizes n = 215 and n = 2265, respectively). The within-breed variation study focused on the level of inbreeding using the ROH-based inbreeding coefficient. The genomic relatedness analyses were carried out among two Estonian and nine European breeds from the WIDDE database. Admixture analysis revealed the heterogeneity of ER cattle with a mixed pattern showing several ancestral populations containing a relatively low proportion (1.5-37.0%) of each of the reference populations used. There was a higher FROH in EH (FROH = 0.115) than in ER (FROH = 0.044). Compared to ER, the long ROHs of EH indicated more closely related parents. The paternal origin of the genetic material used in breeding had a low effect on the inbreeding level. However, among EH, the highest genomic inbreeding was estimated in daughters of USA-born sires.

Genetic insights into crossbred dairy cattle of Pakistan: exploring allele frequency, linkage disequilibrium, and effective population size at a genome-wide scale

Linkage disequilibrium (LD) affects genomic studies accuracy. High-density genotyping platforms identify SNPs across animal genomes, increasing LD evaluation resolution for accurate analysis. This study aimed to evaluate the decay and magnitude of LD in a cohort of 81 crossbred dairy cattle using the GGP_HDv3_C Bead Chip. After quality control, 116,710 Single Nucleotide Polymorphisms (SNPs) across 2520.241 Mb of autosomes were retained. LD extent was assessed between autosomal SNPs within a 10 Mb range using the r2 statistics. LD value declined as inter-marker distance increased. The average r2 value was 0.24 for SNP pairs < 10 kb apart, decreasing to 0.13 for 50-100 kb distances. Minor allele frequency (MAF) and sample size significantly impact LD. Lower MAF thresholds result in smaller r2 values, while higher thresholds show increased r2 values. Additionally, smaller sample sizes exhibit higher average r2 values, especially for larger physical distance intervals (> 50 kb) between SNP pairs. Effective population size and inbreeding coefficient were 150 and 0.028 for the present generation, indicating a decrease in genetic diversity over time. These findings imply that the utilization of high-density SNP panels and customized/breed-specific SNP panels represent a highly favorable approach for conducting genome-wide association studies (GWAS) and implementing genomic selection (GS) in the Bos indicus cattle breeds, whose genomes are still largely unexplored. Furthermore, it is imperative to devise a meticulous breeding strategy tailored to each herd, aiming to enhance desired traits while simultaneously preserving genetic diversity.

The long-term effects of genomic selection: 2. Changes in allele frequencies of causal loci and new mutations

Genetic selection has been applied for many generations in animal, plant, and experimental populations. Selection changes the allelic architecture of traits to create genetic gain. It remains unknown whether the changes in allelic architecture are different for the recently introduced technique of genomic selection compared to traditional selection methods and whether they depend on the genetic architectures of traits. Here, we investigate the allele frequency changes of old and new causal loci under 50 generations of phenotypic, pedigree, and genomic selection, for a trait controlled by either additive, additive and dominance, or additive, dominance, and epistatic effects. Genomic selection resulted in slightly larger and faster changes in allele frequencies of causal loci than pedigree selection. For each locus, allele frequency change per generation was not only influenced by its statistical additive effect but also to a large extent by the linkage phase with other loci and its allele frequency. Selection fixed a large number of loci, and 5 times more unfavorable alleles became fixed with genomic and pedigree selection than with phenotypic selection. For pedigree selection, this was mainly a result of increased genetic drift, while genetic hitchhiking had a larger effect on genomic selection. When epistasis was present, the average allele frequency change was smaller (∼15% lower), and a lower number of loci became fixed for all selection methods. We conclude that for long-term genetic improvement using genomic selection, it is important to consider hitchhiking and to limit the loss of favorable alleles.

Exploring genome-wide differentiation and signatures of selection in Italian and North American Holstein populations

Among Italian dairy cattle, the Holstein is the most reared breed for the production of Parmigiano Reggiano protected designation of origin cheese, which represents one of the most renowned products in the entire Italian dairy industry. In this work, we used a medium-density genome-wide data set consisting of 79,464 imputed SNPs to study the genetic structure of Italian Holstein breed, including the population reared in the area of Parmigiano Reggiano cheese production, and assessing its distinctiveness from the North American population. Multidimensional scaling and ADMIXTURE approaches were used to explore the genetic structure among populations. We also investigated putative genomic regions under selection among these 3 populations by combining 4 different statistical methods based either on allele frequencies (single marker and window-based) or extended haplotype homozygosity (EHH; standardized log-ratio of integrated EHH and cross-population EHH). The genetic structure results allowed us to clearly distinguish the 3 Holstein populations; however, the most remarkable difference was observed between Italian and North American stock. Selection signature analyses identified several significant SNPs falling within or closer to genes with known roles in several traits such as milk quality, resistance to disease, and fertility. In particular, a total of 22 genes related to milk production have been identified using the 2 allele frequency approaches. Among these, a convergent signal has been found in the VPS8 gene which resulted to be involved in milk traits, whereas other genes (CYP7B1, KSR2, C4A, LIPE, DCDC1, GPR20, and ST3GAL1) resulted to be associated with quantitative trait loci related to milk yield and composition in terms of fat and protein percentage. In contrast, a total of 7 genomic regions were identified combining the results of standardized log-ratio of integrated EHH and cross-population EHH. In these regions candidate genes for milk traits were also identified. Moreover, this was also confirmed by the enrichment analyses in which we found that the majority of the significantly enriched quantitative trait loci were linked to milk traits, whereas the gene ontology and pathway enrichment analysis pointed to molecular functions and biological processes involved in AA transmembrane transport and methane metabolism pathway. This study provides information on the genetic structure of the examined populations, showing that they are distinguishable from each other. Furthermore, the selection signature analyses can be considered as a starting point for future studies in the identification of causal mutations and consequent implementation of more practical application.

Impact of kinship matrices on genetic gain and inbreeding with optimum contribution selection in a genomic dairy cattle breeding program

BACKGROUND

Genomic selection has increased genetic gain in dairy cattle, but in some cases it has resulted in higher inbreeding rates. Therefore, there is need for research on efficient management of inbreeding in genomically-selected dairy cattle populations, especially for local breeds with a small population size. Optimum contribution selection (OCS) minimizes the increase in average kinship while it maximizes genetic gain. However, there is no consensus on how to construct the kinship matrix used for OCS and whether it should be based on pedigree or genomic information. VanRaden's method 1 (VR1) is a genomic relationship matrix in which centered genotype scores are scaled with the sum of 2p(1-p) where p is the reference allele frequency at each locus, and VanRaden's method 2 (VR2) scales each locus with 2p(1-p), thereby giving greater weight to loci with a low minor allele frequency. We compared the effects of nine kinship matrices on genetic gain, kinship, inbreeding, genetic diversity, and minor allele frequency when applying OCS in a simulated small dairy cattle population. We used VR1 and VR2, each using base animals, all genotyped animals, and the current generation of animals to compute reference allele frequencies. We also set the reference allele frequencies to 0.5 for VR1 and the pedigree-based relationship matrix. We constrained OCS to select a fixed number of sires per generation for all scenarios. Efficiency of the different matrices were compared by calculating the rate of genetic gain for a given rate of increase in average kinship.

RESULTS

We found that: (i) genomic relationships were more efficient than pedigree-based relationships at managing inbreeding, (ii) reference allele frequencies computed from base animals were more efficient compared to reference allele frequencies computed from recent animals, and (iii) VR1 was slightly more efficient than VR2, but the difference was not statistically significant.

CONCLUSIONS

Using genomic relationships for OCS realizes more genetic gain for a given amount of kinship and inbreeding than using pedigree relationships when the number of sires is fixed. For a small genomic dairy cattle breeding program, we recommend that the implementation of OCS uses VR1 with reference allele frequencies estimated either from base animals or old genotyped animals.

Comparing pedigree and genomic inbreeding coefficients, and inbreeding depression of reproductive traits in Japanese Black cattle

BACKGROUND

Pedigree-based inbreeding coefficients have been generally included in statistical models for genetic evaluation of Japanese Black cattle. The use of genomic data is expected to provide precise assessment of inbreeding level and depression. Recently, many measures have been used for genome-based inbreeding coefficients; however, with no consensus on which is the most appropriate. Therefore, we compared the pedigree- ([Formula: see text]) and multiple genome-based inbreeding coefficients, which were calculated from the genomic relationship matrix with observed allele frequencies ([Formula: see text]), correlation between uniting gametes ([Formula: see text]), the observed vs expected number of homozygous genotypes ([Formula: see text]), runs of homozygosity (ROH) segments ([Formula: see text]) and heterozygosity by descent segments ([Formula: see text]). We quantified inbreeding depression from estimating regression coefficients of inbreeding coefficients on three reproductive traits: age at first calving (AFC), calving difficulty (CD) and gestation length (GL) in Japanese Black cattle.

RESULTS

The highest correlations with [Formula: see text] were for [Formula: see text] (0.86) and [Formula: see text] (0.85) whereas [Formula: see text] and [Formula: see text] provided weak correlations with [Formula: see text], with range 0.33-0.55. Except for [Formula: see text] and [Formula: see text], there were strong correlations among genome-based inbreeding coefficients ([Formula: see text] 0.94). The estimates of regression coefficients of inbreeding depression for [Formula: see text] was 2.1 for AFC, 0.63 for CD and -1.21 for GL, respectively, but [Formula: see text] had no significant effects on all traits. Genome-based inbreeding coefficients provided larger effects on all reproductive traits than [Formula: see text]. In particular, for CD, all estimated regression coefficients for genome-based inbreeding coefficients were significant, and for GL, that for [Formula: see text] had a significant.. Although there were no significant effects when using overall genome-level inbreeding coefficients for AFC and GL, [Formula: see text] provided significant effects at chromosomal level in four chromosomes for AFC, three chromosomes for CD, and two chromosomes for GL. In addition, similar results were obtained for [Formula: see text].

CONCLUSIONS

Genome-based inbreeding coefficients can capture more phenotypic variation than [Formula: see text]. In particular, [Formula: see text] and [Formula: see text] can be considered good estimators for quantifying inbreeding level and identifying inbreeding depression at the chromosome level. These findings might improve the quantification of inbreeding and breeding programs using genome-based inbreeding coefficients.

Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle

Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.

Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information

Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition. Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and three-way crossbred cattle. Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from low-density SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction. Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software.

Reintroducing genetic diversity in populations from cryopreserved material: the case of Abondance, a French local dairy cattle breed

BACKGROUND

Genetic diversity is a necessary condition for populations to evolve under natural adaptation, artificial selection, or both. However, genetic diversity is often threatened, in particular in domestic animal populations where artificial selection, genetic drift and inbreeding are strong. In this context, cryopreserved genetic resources are a promising option to reintroduce lost variants and to limit inbreeding. However, while the use of ancient genetic resources is more common in plant breeding, it is less documented in animals due to a longer generation interval, making it difficult to fill the gap in performance due to continuous selection. This study investigates one of the only concrete cases available in animals, for which cryopreserved semen from a bull born in 1977 in a lost lineage was introduced into the breeding scheme of a French local dairy cattle breed, the Abondance breed, more than 20 years later.

RESULTS

We found that this re-introduced bull was genetically distinct with respect to the current population and thus allowed part of the genetic diversity lost over time to be restored. The expected negative gap in milk production due to continuous selection was absorbed in a few years by preferential mating with elite cows. Moreover, the re-use of this bull more than two decades later did not increase the level of inbreeding, and even tended to reduce it by avoiding mating with relatives. Finally, the reintroduction of a bull from a lost lineage in the breeding scheme allowed for improved performance for reproductive abilities, a trait that was less subject to selection in the past.

CONCLUSIONS

The use of cryopreserved material is an efficient way to manage the genetic diversity of an animal population, by mitigating the effects of both inbreeding and strong selection. However, attention should be paid to mating of animals to limit the disadvantages associated with incorporating original genetic material, notably a discrepancy in the breeding values for selected traits or an increase in inbreeding. Therefore, careful characterization of the genetic resources available in cryobanks could help to ensure the sustainable management of populations, in particular local or small populations. These results could also be transferred to the conservation of wild threatened populations.

Whole-genome sequencing of cryopreserved resources from French Large White pigs at two distinct sampling times reveals strong signatures of convergent and divergent selection between the dam and sire lines

BACKGROUND

Numerous genomic scans for positive selection have been performed in livestock species within the last decade, but often a detailed characterization of the detected regions (gene or trait under selection, timing of selection events) is lacking. Cryopreserved resources stored in reproductive or DNA gene banks offer a great opportunity to improve this characterization by providing direct access to recent allele frequency dynamics, thereby differentiating between signatures from recent breeding objectives and those related to more ancient selection constraints. Improved characterization can also be achieved by using next-generation sequencing data, which helps narrowing the size of the detected regions while reducing the number of associated candidate genes.

METHODS

We estimated genetic diversity and detected signatures of recent selection in French Large White pigs by sequencing the genomes of 36 animals from three distinct cryopreserved samples: two recent samples from dam (LWD) and sire (LWS) lines, which had diverged from 1995 and were selected under partly different objectives, and an older sample from 1977 prior to the divergence.

RESULTS

French LWD and LWS lines have lost approximately 5% of the SNPs that segregated in the 1977 ancestral population. Thirty-eight genomic regions under recent selection were detected in these lines and the corresponding selection events were further classified as convergent between lines (18 regions), divergent between lines (10 regions), specific to the dam line (6 regions) or specific to the sire line (4 regions). Several biological functions were found to be significantly enriched among the genes included in these regions: body size, body weight and growth regardless of the category, early life survival and calcium metabolism more specifically in the signatures in the dam line and lipid and glycogen metabolism more specifically in the signatures in the sire line. Recent selection on IGF2 was confirmed and several other regions were linked to a single candidate gene (ARHGAP10, BMPR1B, GNA14, KATNA1, LPIN1, PKP1, PTH, SEMA3E or ZC3HAV1, among others).

CONCLUSIONS

These results illustrate that sequencing the genome of animals at several recent time points generates considerable insight into the traits, genes and variants under recent selection in a population. This approach could be applied to other livestock populations, e.g. by exploiting the rich biological resources stored in cryobanks.

Estimating inbreeding rate and effective population size in the Finnish Ayrshire population in the era of genomic selection

Genomic selection has been applied in dairy cattle breeding over the last decade. Using genomic information may speed up genetic gain as breeding values can be predicted reasonably accurately directly after birth. However, genetic diversity may decrease if the inbreeding rate per generation increases and the effective population size decreases. Despite many positive qualities of the Finnish Ayrshire, for example, high average protein yield and fertility, over time the breed has lost its place as the most common dairy breed in Finland. Thus, maintaining the genetic variability of the breed is becoming more important. The aim of our research was to estimate the impact of genomic selection on inbreeding rate and effective population size using both pedigree and genomic data. The genomic data included 46,914 imputed single nucleotide polymorphism (SNP) variants from 75,038 individuals, and the pedigree data included 2,770,025 individuals. All animals in the data were born between 2000 and 2020. Genomic inbreeding coefficients were estimated as the proportion of SNPs in runs of homozygosity (ROH) out of the total number of SNPs. The inbreeding rate was estimated by regressing the mean genomic inbreeding coefficients on birth years. Effective population size was then estimated based on the inbreeding rate. Additionally, effective population size was estimated from the mean increase in individual inbreeding using pedigree data. Introduction of genomic selection was assumed to have taken place gradually; years 2012-2014 were treated as a transition period from the traditional phenotype-based breeding value estimation to genomic-based estimation. The median length of the identified homozygous segments was 5.5 Mbp, and a slight increase in the proportion of segments over 10 Mbp was observed after 2010. The inbreeding rate decreased from 2000 to 2011 and subsequently increased slightly. The pedigree- and genomic-based estimates of inbreeding rate were similar to each other. The estimates of effective population size based on the regression method were very sensitive to the number of years considered; thus, the estimates were not very reliable. The effective population size estimated from the mean increase in individual inbreeding reached its highest value of 160 in 2011 and decreased to 150 after that. In addition, the generation interval in the sire path has decreased from 5.5 years to 3.5 years after genomic selection was implemented. Based on our results, after the implementation of genomic selection, the proportion of long ROH stretches has increased, the generation interval in the sire path has decreased, the inbreeding rate has increased and the effective population size has decreased. However, the effective population size is still at a good level, allowing for an efficient selection scheme in the Finnish Ayrshire breed.

Weighted kernels improve multi-environment genomic prediction

Crucial to variety improvement programs is the reliable and accurate prediction of genotype's performance across environments. However, due to the impactful presence of genotype by environment (G×E) interaction that dictates how changes in expression and function of genes influence target traits in different environments, prediction performance of genomic selection (GS) using single-environment models often falls short. Furthermore, despite the successes of genome-wide association studies (GWAS), the genetic insights derived from genome-to-phenome mapping have not yet been incorporated in predictive analytics, making GS models that use Gaussian kernel primarily an estimator of genomic similarity, instead of the underlying genetics characteristics of the populations. Here, we developed a GS framework that, in addition to capturing the overall genomic relationship, can capitalize on the signal of genetic associations of the phenotypic variation as well as the genetic characteristics of the populations. The capacity of predicting the performance of populations across environments was demonstrated by an overall gain in predictability up to 31% for the winter wheat DH population. Compared to Gaussian kernels, we showed that our multi-environment weighted kernels could better leverage the significance of genetic associations and yielded a marked improvement of 4-33% in prediction accuracy for half-sib families. Furthermore, the flexibility incorporated in our Bayesian implementation provides the generalizable capacity required for predicting multiple highly genetic heterogeneous populations across environments, allowing reliable GS for genetic improvement programs that have no access to genetically uniform material.

A comparison of marker-based estimators of inbreeding and inbreeding depression

BACKGROUND

The availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (F_LH1 and F_LH2), VanRaden (F_VR1 and F_VR2), Yang and colleagues (F_YA1 and F_YA2), marker homozygosity (F_HOM), runs of homozygosity (F_ROH) and estimates based on pedigree (F_PED) in comparison with estimates obtained from IBD measures (F_IBD).

RESULTS

If the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with F_IBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with F_IBD is generally obtained by F_LH1 and the best estimator of ΔID is F_YA2. The estimators F_VR2 and F_LH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with F_IBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (F_HOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (F_ROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (F_PED) show a lower correlation with F_IBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations.

CONCLUSIONS

When base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with F_IBD and provide good estimates of ΔID. When base population allele frequencies are unknown, F_LH1 is the marker frequency-based estimator that is most correlated with F_IBD, and F_YA2 provides the most accurate estimates of ΔID. Estimates from F_ROH are also very precise in most scenarios. The estimators F_VR2 and F_LH2 have the poorest performances.

Fitting Genomic Prediction Models with Different Marker Effects among Prefectures to Carcass Traits in Japanese Black Cattle

We fitted statistical models, which assumed single-nucleotide polymorphism (SNP) marker effects differing across the fattened steers marketed into different prefectures, to the records for cold carcass weight (CW) and marbling score (MS) of 1036, 733, and 279 Japanese Black fattened steers marketed into Tottori, Hiroshima, and Hyogo prefectures in Japan, respectively. Genotype data on 33,059 SNPs was used. Five models that assume only common SNP effects to all the steers (model 1), common effects plus SNP effects differing between the steers marketed into Hyogo prefecture and others (model 2), only the SNP effects differing between Hyogo steers and others (model 3), common effects plus SNP effects specific to each prefecture (model 4), and only the effects specific to each prefecture (model 5) were exploited. For both traits, slightly lower values of residual variance than that of model 1 were estimated when fitting all other models. Estimated genetic correlation among the prefectures in models 2 and 4 ranged to 0.53 to 0.71, all <0.8. These results might support that the SNP effects differ among the prefectures to some degree, although we discussed the necessity of careful consideration to interpret the current results.

Integrative QTL mapping and selection signatures in Groningen White Headed cattle inferred from whole-genome sequences

Here, we aimed to identify and characterize genomic regions that differ between Groningen White Headed (GWH) breed and other cattle, and in particular to identify candidate genes associated with coat color and/or eye-protective phenotypes. Firstly, whole genome sequences of 170 animals from eight breeds were used to evaluate the genetic structure of the GWH in relation to other cattle breeds by carrying out principal components and model-based clustering analyses. Secondly, the candidate genomic regions were identified by integrating the findings from: a) a genome-wide association study using GWH, other white headed breeds (Hereford and Simmental), and breeds with a non-white headed phenotype (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel, Dutch Belted, and Holstein Friesian); b) scans for specific signatures of selection in GWH cattle by comparison with four other Dutch traditional breeds (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel and Dutch Belted) and the commercial Holstein Friesian; and c) detection of candidate genes identified via these approaches. The alignment of the filtered reads to the reference genome (ARS-UCD1.2) resulted in a mean depth of coverage of 8.7X. After variant calling, the lowest number of breed-specific variants was detected in Holstein Friesian (148,213), and the largest in Deep Red (558,909). By integrating the results, we identified five genomic regions under selection on BTA4 (70.2-71.3 Mb), BTA5 (10.0-19.7 Mb), BTA20 (10.0-19.9 and 20.0-22.7 Mb), and BTA25 (0.5-9.2 Mb). These regions contain positional and functional candidate genes associated with retinal degeneration (e.g., CWC27 and CLUAP1), ultraviolet protection (e.g., ERCC8), and pigmentation (e.g. PDE4D) which are probably associated with the GWH specific pigmentation and/or eye-protective phenotypes, e.g. Ambilateral Circumocular Pigmentation (ACOP). Our results will assist in characterizing the molecular basis of GWH phenotypes and the biological implications of its adaptation.

Inbreeding and pedigree analysis of the European red dairy cattle

BACKGROUND

Red dairy cattle breeds have an important role in the European dairy sector because of their functional characteristics and good health. Extensive pedigree information is available for these breeds and provides a unique opportunity to examine their population structure, such as effective population size, depth of the pedigree, and effective number of founders and ancestors, and inbreeding levels. Animals with the highest genetic contributions were identified. Pedigree data included 9,073,403 animals that were born between 1900 and 2019 from Denmark, Finland, Germany, Latvia, Lithuania, the Netherlands, Norway, Poland, and Sweden, and covered 32 breeds. The numerically largest breeds were Red Dairy Cattle and Meuse-Rhine-Yssel.

RESULTS

The deepest average complete generation equivalent (9.39) was found for Red Dairy Cattle in 2017. Mean pedigree completeness ranged from 0.6 for Finncattle to 7.51 for Red Dairy Cattle. An effective population size of 166 animals was estimated for the total pedigree and ranged from 35 (Rotes Höhenvieh) to 226 (Red Dairy Cattle). Average generation intervals were between 5 and 7 years. The mean inbreeding coefficient for animals born between 1960 and 2018 was 1.5%, with the highest inbreeding coefficients observed for Traditional Angler (4.2%) and Rotes Höhenvieh (4.1%). The most influential animal was a Dutch Meuse-Rhine-Yssel bull born in 1960. The mean inbreeding level for animals born between 2016 and 2018 was 2% and highest for the Meuse-Rhine-Yssel (4.64%) and Rotes Hohenvieh breeds (3.80%).

CONCLUSIONS

We provide the first detailed analysis of the genetic diversity and inbreeding levels of the European red dairy cattle breeds. Rotes Höhenvieh and Traditional Angler have high inbreeding levels and are either close to or below the minimal recommended effective population size, thus it is necessary to implement tools to monitor the selection process in order to control inbreeding in these breeds. Red Dairy Cattle, Vorderwälder, Swedish Polled and Hinterwälder hold more genetic diversity. Regarding the Meuse-Rhine-Yssel breed, given its decreased population size, increased inbreeding and low effective population size, we recommend implementation of a breeding program to prevent further loss in its genetic diversity.

Genomic characterization of autozygosity and recent inbreeding trends in all major breeds of US dairy cattle

Maintaining a genetically diverse dairy cattle population is critical to preserving adaptability to future breeding goals and avoiding declines in fitness. This study characterized the genomic landscape of autozygosity and assessed trends in genetic diversity in 5 breeds of US dairy cattle. We analyzed a sizable genomic data set containing 4,173,679 pedigreed and genotyped animals of the Ayrshire, Brown Swiss, Guernsey, Holstein, and Jersey breeds. Runs of homozygosity (ROH) of 2 Mb or longer in length were identified in each animal. The within-breed means for number and the combined length of ROH were highest in Jerseys (62.66 ± 8.29 ROH and 426.24 ± 83.40 Mb, respectively; mean ± SD) and lowest in Ayrshires (37.24 ± 8.27 ROH and 265.05 ± 85.00 Mb, respectively). Short ROH were the most abundant, but moderate to large ROH made up the largest proportion of genome autozygosity in all breeds. In addition, we identified ROH islands in each breed. This revealed selection patterns for milk production, productive life, health, and reproduction in most breeds and evidence for parallel selective pressure for loci on chromosome 6 between Ayrshire and Brown Swiss and for loci on chromosome 20 between Holstein and Jersey. We calculated inbreeding coefficients using 3 different approaches, pedigree-based (F_PED), marker-based using a genomic relationship matrix (F_GRM), and segment-based using ROH (F_ROH). The average inbreeding coefficient ranged from 0.06 in Ayrshires and Brown Swiss to 0.08 in Jerseys and Holsteins using F_PED, from 0.22 in Holsteins to 0.29 in Guernsey and Jerseys using F_GRM, and from 0.11 in Ayrshires to 0.17 in Jerseys using F_ROH. In addition, the effective population size at past generations (5-100 generations ago), the yearly rate of inbreeding, and the effective population size in 3 recent periods (2000-2009, 2010-2014, and 2015-2018) were determined in each breed to ascertain current and historical trends of genetic diversity. We found a historical trend of decreasing effective population size in the last 100 generations in all breeds and breed differences in the effect of the recent implementation of genomic selection on inbreeding accumulation.

Opportunities of Genomics for the Use of Semen Cryo-Conserved in Gene Banks

Shortly after the introduction of cryo-conserved semen in the main farm animal species, gene banks were founded. Safeguarding farm animal genetic diversity for future use was and is the main objective. A sampling of sires was based on their pedigree and phenotypic information. Nowadays, DNA information from cryo-conserved sires and from animals in the living populations has become available. The combination of their DNA information can be used to realize three opportunities: 1) to make the gene bank a more complete archive of genetic diversity, 2) to determine the history of the genetic diversity from the living populations, and 3) to improve the performance and genetic diversity of living populations. These three opportunities for the use of gene bank sires in the genomic era are outlined in this study, and relevant recent literature is summarized to illustrate the great value of a gene bank as an archive of genetic diversity.

Estimation of the autosomal contribution to total additive genetic variability of carcass traits in Japanese Black cattle

We attempted to estimate the additive genetic variance explained by each autosome, using genotype data of 33,657 single nucleotide polymorphism (SNP) markers in 2271 Japanese Black fattened steers. Traits were cold carcass weight, ribeye area, rib thickness, subcutaneous fat thickness, estimated yield percentage, and marbling score. Two mixed linear models were used: One is that (model 1) incorporating a genomic relationship matrix (G matrix) constructed by using all available SNPs, and another (model 2), incorporating two G matrices constructed by using the SNPs on one autosome and using those on the remaining autosomes. Genomic heritabilities estimated using model 1 were moderate to high. The sums of the proportions of the additive genetic variance explained by each autosome to the total genetic variance estimated by using model 2 were >90%. For carcass weight, the proportions explained by Bos taurus autosomes 6, 8, and 14 were higher than those explained by the remaining autosomes. In some cases, the estimated proportion was close to 0. The results obtained from model 2 could provide a novel insight into the genetic architecture, such as heritability per chromosome, of carcass traits in Japanese Black cattle, although further careful investigation would be required.

The long-term effects of genomic selection: 1. Response to selection, additive genetic variance, and genetic architecture

Background

Genomic selection has revolutionized genetic improvement in animals and plants, but little is known about its long-term effects. Here, we investigated the long-term effects of genomic selection on response to selection, genetic variance, and the genetic architecture of traits using stochastic simulations. We defined the genetic architecture as the set of causal loci underlying each trait, their allele frequencies, and their statistical additive effects. We simulated a livestock population under 50 generations of phenotypic, pedigree, or genomic selection for a single trait, controlled by either only additive, additive and dominance, or additive, dominance, and epistatic effects. The simulated epistasis was based on yeast data.

Results

Short-term response was always greatest with genomic selection, while response after 50 generations was greater with phenotypic selection than with genomic selection when epistasis was present, and was always greater than with pedigree selection. This was mainly because loss of genetic variance and of segregating loci was much greater with genomic and pedigree selection than with phenotypic selection. Compared to pedigree selection, selection response was always greater with genomic selection. Pedigree and genomic selection lost a similar amount of genetic variance after 50 generations of selection, but genomic selection maintained more segregating loci, which on average had lower minor allele frequencies than with pedigree selection. Based on this result, genomic selection is expected to better maintain genetic gain after 50 generations than pedigree selection. The amount of change in the genetic architecture of traits was considerable across generations and was similar for genomic and pedigree selection, but slightly less for phenotypic selection. Presence of epistasis resulted in smaller changes in allele frequencies and less fixation of causal loci, but resulted in substantial changes in statistical additive effects across generations.

Conclusions

Our results show that genomic selection outperforms pedigree selection in terms of long-term genetic gain, but results in a similar reduction of genetic variance. The genetic architecture of traits changed considerably across generations, especially under selection and when non-additive effects were present. In conclusion, non-additive effects had a substantial impact on the accuracy of selection and long-term response to selection, especially when selection was accurate.

Genetic Diversity in the Italian Holstein Dairy Cattle Based on Pedigree and SNP Data Prior and After Genomic Selection

Genetic diversity has become an urgent matter not only in small local breeds but also in more specialized ones. While the use of genomic data in livestock breeding programs increased genetic gain, there is increasing evidence that this benefit may be counterbalanced by the potential loss of genetic variability. Thus, in this study, we aimed to investigate the genetic diversity in the Italian Holstein dairy cattle using pedigree and genomic data from cows born between 2002 and 2020. We estimated variation in inbreeding, effective population size, and generation interval and compared those aspects prior to and after the introduction of genomic selection in the breed. The dataset contained 84,443 single-nucleotide polymorphisms (SNPs), and 74,485 cows were analyzed. Pedigree depth based on complete generation equivalent was equal to 10.67. A run of homozygosity (ROH) analysis was adopted to estimate SNP-based inbreeding (F_ROH). The average pedigree inbreeding was 0.07, while the average F_ROH was more than double, being equal to 0.17. The pattern of the effective population size based on pedigree and SNP data was similar although different in scale, with a constant decrease within the last five generations. The overall inbreeding rate (ΔF) per year was equal to +0.27% and +0.44% for F_ped and F_ROH throughout the studied period, which corresponded to about +1.35% and +2.2% per generation, respectively. A significant increase in the ΔF was found since the introduction of genomic selection in the breed. This study in the Italian Holstein dairy cattle showed the importance of controlling the loss of genetic diversity to ensure the long-term sustainability of this breed, as well as to guarantee future market demands.

How genomic selection has increased rates of genetic gain and inbreeding in the Australian national herd, genomic information nucleus, and bulls

Genomic selection has been commonly used for selection for over a decade. In this time, the rate of genetic gain has more than doubled in some countries, while inbreeding per year has also increased. Inbreeding can result in a loss of genetic diversity, decreased long-term response to selection, reduced animal performance and ultimately, decreased farm profitability. We quantified and compared changes in genetic gain and diversity resulting from genomic selection in Australian Holstein and Jersey cattle populations. To increase the accuracy of genomic selection, Australia has had a female genomic reference population since 2013, specifically designed to be representative of commercial populations and thus including both Holstein and Jersey cows. Herds that kept excellent health and fertility data were invited to join this population and most their animals were genotyped. In both breeds, the rate of genetic gain and inbreeding was greatest in bulls, and then the female genomic reference population, and finally the wider national herd. When comparing pre- and postgenomic selection, the rates of genetic gain for the national economic index has increased by ~160% in Holstein females and ~100% in Jersey females. This has been accompanied by doubling of the rates of inbreeding in female populations, and the rate of inbreeding has increased several fold in Holstein bulls since the widespread use of genomic selection. Where cow genotype data were available to perform a more accurate genomic analysis, greater rates of pedigree and genomic inbreeding were observed, indicating actual inbreeding levels could be underestimated in the national population due to gaps in pedigrees. Based on current rates of genetic gain, the female reference population is progressing ahead of the national herd and could be used to infer and track the future inbreeding and genetic trends of the national herds.

Trends in genetic diversity and the effect of inbreeding in American Angus cattle under genomic selection

Background

While the adoption of genomic evaluations in livestock has increased genetic gain rates, its effects on genetic diversity and accumulation of inbreeding have raised concerns in cattle populations. Increased inbreeding may affect fitness and decrease the mean performance for economically important traits, such as fertility and growth in beef cattle, with the age of inbreeding having a possible effect on the magnitude of inbreeding depression. The purpose of this study was to determine changes in genetic diversity as a result of the implementation of genomic selection in Angus cattle and quantify potential inbreeding depression effects of total pedigree and genomic inbreeding, and also to investigate the impact of recent and ancient inbreeding.

Results

We found that the yearly rate of inbreeding accumulation remained similar in sires and decreased significantly in dams since the implementation of genomic selection. Other measures such as effective population size and the effective number of chromosome segments show little evidence of a detrimental effect of using genomic selection strategies on the genetic diversity of beef cattle. We also quantified pedigree and genomic inbreeding depression for fertility and growth. While inbreeding did not affect fertility, an increase in pedigree or genomic inbreeding was associated with decreased birth weight, weaning weight, and post-weaning gain in both sexes. We also measured the impact of the age of inbreeding and found that recent inbreeding had a larger depressive effect on growth than ancient inbreeding.

Conclusions

In this study, we sought to quantify and understand the possible consequences of genomic selection on the genetic diversity of American Angus cattle. In both sires and dams, we found that, generally, genomic selection resulted in decreased rates of pedigree and genomic inbreeding accumulation and increased or sustained effective population sizes and number of independently segregating chromosome segments. We also found significant depressive effects of inbreeding accumulation on economically important growth traits, particularly with genomic and recent inbreeding.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00644-z.

The value of genomic relationship matrices to estimate levels of inbreeding

BACKGROUND

Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (FNEJ), the Li and Horvitz matrix based on excess of homozygosity (FL&H), and the VanRaden (methods 1, FVR1, and 2, FVR2) and Yang (FYAN) genomic relationship matrices. We derived expectations for each inbreeding coefficient, assuming a single locus model, and used these expectations to explain the patterns of the coefficients that were computed from thousands of single nucleotide polymorphism genotypes in a population of Iberian pigs.

RESULTS

Except for FNEJ, the evaluated measures of inbreeding do not match with the original definitions of inbreeding coefficient of Wright (correlation) or Malécot (probability). When inbreeding coefficients are interpreted as indicators of variability (heterozygosity) that was gained or lost relative to a base population, both FNEJ and FL&H led to sensible results but this was not the case for FVR1, FVR2 and FYAN. When variability has increased relative to the base, FVR1, FVR2 and FYAN can indicate that it decreased. In fact, based on FYAN, variability is not expected to increase. When variability has decreased, FVR1 and FVR2 can indicate that it has increased. Finally, these three coefficients can indicate that more variability than that present in the base population can be lost, which is also unreasonable. The patterns for these coefficients observed in the pig population were very different, following the derived expectations. As a consequence, the rate of inbreeding depression estimated based on these inbreeding coefficients differed not only in magnitude but also in sign.

CONCLUSIONS

Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.

Genomic inbreeding and selection signatures in the local dairy breed Icelandic Cattle

Icelandic Cattle is the only dairy cattle breed native to Iceland. It currently numbers ca. 26 000 breeding females. We used 50k genotypes of over 8000 Icelandic Cattle to estimate genomic and pedigree-based inbreeding and to detect selection signatures using the integrated haplotype score. We used 47 Icelandic bulls genotyped with a 770k SNP chip to estimate LD decay for comparison with other Nordic dairy cattle breeds. We detected ROHs on the autosomes and computed ROH-based autosomal inbreeding coefficients. Average inbreeding coefficients according to pedigree and ROHs were 0.0621 and 0.101. Effective population sizes for the years 2009-2017 according to pedigree, ROHs, genomic relationship matrix, excess of homozygosity and individual increase in inbreeding were 81, 65, 60, 58 and 92 respectively. We identified three regions and six candidate genes that showed a signature of selection according to the integrated haplotype score (P < 0.05) on chromosomes 1, 16 and 23. The LD structure of Icelandic Cattle is shaped by a long period of isolation and a small founder population. The estimate of LD at distances closer than 0.3 Mb is lower in Icelandic Cattle than in Danish Jersey, but is higher than in Danish Holstein and Red Nordic Dairy Cattle breeds. Our findings show that inbreeding rates in Icelandic Cattle currently are sustainable according to FAO guidelines, and our results do not indicate severe historical inbreeding.

Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle

BACKGROUND

Inbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH).

METHODS

Genotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations.

RESULTS

Genome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found.

CONCLUSIONS

Inbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.

Intensified Use of Reproductive Technologies and Reduced Dimensions of Breeding Schemes Put Genetic Diversity at Risk in Dairy Cattle Breeds

In the management of dairy cattle breeds, two recent trends have arisen that pose potential threats to genetic diversity: the use of reproductive technologies (RT) and a reduction in the number of bulls in breeding schemes. The expected outcome of these changes, in terms of both genetic gain and genetic diversity, is not trivial to predict. Here, we simulated 15 breeding schemes similar to those carried out in large French dairy cattle breeds; breeding schemes differed with respect to their dimensions, the intensity of RT use, and the type of RT involved. We found that intensive use of RT resulted in improved genetic gain, but deteriorated genetic diversity. Specifically, a reduction in the interval between generations through the use of ovum pick-up and in vitro fertilization (OPU-IVF) resulted in a large increase in the inbreeding rate both per year and per generation, suggesting that OPU-IVF could have severe adverse effects on genetic diversity. To achieve a given level of genetic gain, the scenarios that best maintained genetic diversity were those with a higher number of sires/bulls and a medium intensity of RT use or those with a higher number of female donors to compensate for the increased intensity of RT.

Long-Term Evaluation of Breeding Scheme Alternatives for Endangered Honeybee Subspecies

Modern breeding structures are emerging for European honeybee populations. However, while genetic evaluations of honeybees are becoming increasingly well understood, little is known about how selection decisions shape the populations' genetic structures. We performed simulations evaluating 100 different selection schemes, defined by selection rates for dams and sires, in populations of 200, 500, or 1000 colonies per year and considering four different quantitative traits, reflecting different genetic parameters and numbers of influential loci. Focusing on sustainability, we evaluated genetic progress over 100 years and related it to inbreeding developments. While all populations allowed for sustainable breeding with generational inbreeding rates below 1% per generation, optimal selection rates differed and sustainable selection was harder to achieve in smaller populations and for stronger negative correlations of maternal and direct effects in the selection trait. In small populations, a third or a fourth of all candidate queens should be selected as dams, whereas this number declined to a sixth for larger population sizes. Furthermore, our simulations indicated that, particularly in small populations, as many sires as possible should be provided. We conclude that carefully applied breeding provides good prospects for currently endangered honeybee subspecies, since sustainable genetic progress improves their attractiveness to beekeepers.

Effect of genomic selection on rate of inbreeding and coancestry and effective population size of Holstein and Jersey cattle populations

Genetic diversity in livestock populations is a significant contributor to the sustainability of animal production. Also, genetic diversity allows animal production to become more responsive to environmental changes and market demands. The loss of genetic diversity can result in a plateau in production and may also result in loss of fitness or viability in animal production. In this study, we investigated the rate of inbreeding (ΔF), rate of coancestry (Δf), and effective population size (N_e) as important quantitative indicators of genetic diversity and evaluated the effect of the recent implementation of genomic selection on the loss of genetic diversity in North American Holstein and Jersey dairy cattle. To estimate the rate of inbreeding and coancestry, inbreeding and coancestry coefficients were calculated using the traditional pedigree method and genomic methods estimated from segment- and marker-based approaches. Furthermore, we estimated N_e from the rate of inbreeding and coancestry and extent of linkage disequilibrium. A total of 205,755 and 89,238 pedigreed and genotyped animals born between 1990 and 2018 inclusively were available for Holsteins and Jerseys, respectively. The estimated average pedigree inbreeding coefficients were 7.74 and 7.20% for Holsteins and Jerseys, respectively. The corresponding values for the segment and marker-by-marker genomic inbreeding coefficients were 13.61, 15.64, and 31.40% for Holsteins and 21.16, 22.54, and 42.62% for Jerseys, respectively. The average coancestry coefficients were 8.33 and 15.84% for Holsteins and 9.23 and 23.46% for Jerseys with pedigree and genomic measures, respectively. Generation interval for the whole 29-yr time period averaged approximately 5 yr for all selection pathways combined. The ΔF per generation based on pedigree, segment, and marker-by-marker genomic measures for the entire 29-yr period was estimated to be 0.75, 1.10, 1.16, and 1.02% for Holstein animals and 0.67, 0.62, 0.63, and 0.59% for Jersey animals, respectively. The Δf was estimated to be 0.98 and 0.98% for Holsteins and 0.73 and 0.78% for Jerseys with pedigree and genomic measures, respectively. These ΔF and Δf translated to an N_e that ranged from 43 to 66 animals for Holsteins and 64 to 85 animals for Jerseys. In addition, the N_e based on linkage disequilibrium was 58 and 120 for Holsteins and Jerseys, respectively. The 10-yr period that involved the application of genomic selection resulted in an increased ΔF per generation with ranges from 1.19 to 2.06% for pedigree and genomic measures in Holsteins. Given the rate at which inbreeding is increasing after the implementation of genomic selection, there is a need to implement measures and means for controlling the rate of inbreeding per year, which will help to manage and maintain farm animal genetic resources.

Inbreeding in a Population of Polish Holstein-Friesian Young Bulls Before and After Genomic Selection

Inbreeding was analysed in a population of 14,144 Polish Black-and-White Holstein-Friesian (PBWHF) young bulls born between 1994 and 2017 and bred under both conventional and genomic breeding programmes. The inbreeding coefficients were computed using a model with genetic groups, according to the algorithm given by VanRaden. It was found that in the analysed population all bulls are inbred (100% of the population), with the mean coefficient of inbreeding ranging from 0.09% to 26.95%. Pedigree analysis also showed a relationship between the changing number of bulls over the years and the dynamics of population inbreeding. These trends are connected with changes in the breeding scheme, related to the implementation of genomic selection in the breeding programme for PBWHF cattle in 2014. The increasing number of weaned young bulls in Poland was paralleled by a fairly consistent increase in the mean inbreeding, but the inbreeding dynamics were relatively small. A reverse trend was observed in the group of young bulls born after 2013. As the number of bulls very rapidly decreased in successive birth years, the mean inbreeding for successive birth-year groups very rapidly increased. As a result, the estimated linear trend was equal to 0.02% inbreeding per year of birth in the group of bulls raised before genomic selection (~20 birth-year) whereas in the group of bulls raised after genomic selection (~4 birth-year) the trend was much higher and amounted to 0.56% inbreeding per year of birth. The high mean inbreeding found in the group of the genomically selected young bulls may translate into higher inbreeding in the whole population of PBWHF cattle, because these bulls are now intensively used as sires. The results of our study also show that the implementation of genomic selection in the breeding programme caused a very rapid increase in the inbreeding rate per birth-year in young bulls.

Exploring insertions and deletions (indels) of MSRB3 gene and their association with growth traits in four Chinese indigenous cattle breeds

Methionine sulfoxide reductase B3 (MSRB3) is instrumental in ossification and fat deposition, which regulate the growth and development of cattle directly. The purpose of this study was aimed to explore insertions and deletions (indels) in MSRB3 gene and investigate their association with growth traits in four indigenous cattle breeds (Luxi cattle, Qinchuan cattle, Nanyang cattle, and Jiaxian Red cattle). Four indels were identified by sequencing with DNA pool. Association analysis showed that three of them were associated with growth traits (P<0.05). For P1, the DD (deletion and deletion) genotype was significantly associated with body length of Nanyang cattle; for P6, II (insertion and insertion) and/or DD genotypes were significantly associated with enhanced growth traits of Qinchuan cattle; for P7, II genotype was significantly associated with hucklebone width of Luxi cattle. Our results demonstrated that the polymorphisms in bovine MSRB3 gene were significantly associated with growth traits, which could be candidate loci for marker-assisted selection (MAS) in cattle breeding.

Characterization of Genetic Diversity Conserved in the Gene Bank for Dutch Cattle Breeds

In this study, we characterized genetic diversity in the gene bank for Dutch native cattle breeds. A total of 715 bulls from seven native breeds and a sample of 165 Holstein Friesian bulls were included. Genotype data were used to calculate genetic similarities. Based on these similarities, most breeds were clearly differentiated, except for two breeds (Deep Red and Improved Red and White) that have recently been derived from the MRY breed, and for the Dutch Friesian and Dutch Friesian Red, which have frequently exchanged bulls. Optimal contribution selection (OCS) was used to construct core sets of bulls with a minimized similarity. The composition of the gene bank appeared to be partly optimized in the semen collection process, i.e., the mean similarity within breeds based on the current number of straws per bull was 0.32% to 1.49% lower than when each bull would have contributed equally. Mean similarity could be further reduced within core sets by 0.34% to 2.79% using OCS. Material not needed for the core sets can be made available for supporting in situ populations and for research. Our findings provide insight in genetic diversity in Dutch cattle breeds and help to prioritize material in gene banking.

Genotyping more cows increases genetic gain and reduces rate of true inbreeding in a dairy cattle breeding scheme using female reproductive technologies

Both small dairy cattle populations and dairy cattle populations with a low level of linkage disequilibrium (LD) suffer from low reliability of genomic prediction. In this study, we investigated whether adding more genotyped cows to the reference population influences the rate of genetic gain and rate of inbreeding by affecting the reliability. A standard breeding program with a large reference population and high LD, which mimicked a breeding program for Danish Holstein population, was simulated as a reference. A Danish Jersey population with a small reference population and high LD and a Red Dairy Cattle population with a large reference population and low LD were also simulated. Two additional breeding programs were simulated for Danish Jersey and Red Dairy Cattle populations, where 2,000 additional genotyped cows were included in the population for genomic selection. All 5 simulated breeding programs were initiated by a founder population to generate LD resembling the real LD pattern, followed by a 20-yr conventional progeny-testing scheme with 1,000 or 10,000 genotyped progeny-tested bulls and a 10-yr genomic selection scheme with or without 2,000 additional genotyped cows. Evaluation criteria were annual monetary genetic gain and rate of true inbreeding. Our results showed that adding more genotyped cows to the reference in dairy cattle populations has the potential to increase genetic gain and reduce the rate of inbreeding, regardless of reference population size and level of LD. However, it is still not possible to reach the same genetic gain as in the simulated Danish Holstein population with either a small reference population or low LD. Our results also showed that in a small reference population with high LD, it is difficult to manage inbreeding because of lower accuracy compared with the simulated Danish Holstein population and a smaller number of relevant families to select from. Therefore, breeding strategies need to be chosen to match population size and structure. The rate of true inbreeding is always underestimated by pedigree inbreeding and even more in genomic breeding programs, indicating that some forms of genome-wide inbreeding, instead of pedigree-based inbreeding, should be used to monitor inbreeding when genomic selection is implemented.

The Impact of Genomic and Traditional Selection on the Contribution of Mutational Variance to Long-Term Selection Response and Genetic Variance

De novo mutations (DNM) create new genetic variance and are an important driver for long-term selection response. We hypothesized that genomic selection exploits mutational variance less than traditional selection methods such as mass selection or selection on pedigree-based breeding values, because DNM in selection candidates are not captured when the selection candidates' own phenotype is not used in genomic selection, DNM are not on SNP chips and DNM are not in linkage disequilibrium with the SNP on the chip. We tested this hypothesis with Monte Carlo simulation. From whole-genome sequence data, a subset of ∼300,000 variants was used that served as putative markers, quantitative trait loci or DNM. We simulated 20 generations with truncation selection based on breeding values from genomic best linear unbiased prediction without (GBLUP_no_OP) or with own phenotype (GBLUP_OP), pedigree-based BLUP without (BLUP_no_OP) or with own phenotype (BLUP_OP), or directly on phenotype. GBLUP_OP was the best strategy in exploiting mutational variance, while GBLUP_no_OP and BLUP_no_OP were the worst in exploiting mutational variance. The crucial element is that GBLUP_no_OP and BLUP_no_OP puts no selection pressure on DNM in selection candidates. Genetic variance decreased faster with GBLUP_no_OP and GBLUP_OP than with BLUP_no_OP, BLUP_OP or mass selection. The distribution of mutational effects, mutational variance, number of DNM per individual and nonadditivity had a large impact on mutational selection response and mutational genetic variance, but not on ranking of selection strategies. We advocate that more sustainable genomic selection strategies are required to optimize long-term selection response and to maintain genetic diversity.

Inbreeding depression due to recent and ancient inbreeding in Dutch Holstein-Friesian dairy cattle

Background

Inbreeding decreases animal performance (inbreeding depression), but not all inbreeding is expected to be equally harmful. Recent inbreeding is expected to be more harmful than ancient inbreeding, because selection decreases the frequency of deleterious alleles over time. Selection efficiency is increased by inbreeding, a process called purging. Our objective was to investigate effects of recent and ancient inbreeding on yield, fertility and udder health traits in Dutch Holstein–Friesian cows.

Methods

In total, 38,792 first-parity cows were included. Pedigree inbreeding (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{PED}$$\end{document}FPED) was computed and 75 k genotype data were used to compute genomic inbreeding, among others based on regions of homozygosity (ROH) in the genome (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{ROH}$$\end{document}FROH).

Results

Inbreeding depression was observed, e.g. a 1% increase in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{ROH}$$\end{document}FROH was associated with a 36.3 kg (SE = 2.4) decrease in 305-day milk yield, a 0.48 day (SE = 0.15) increase in calving interval and a 0.86 unit (SE = 0.28) increase in somatic cell score for day 150 through to 400. These effects equalled − 0.45, 0.12 and 0.05% of the trait means, respectively. When \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{PED}$$\end{document}FPED was split into generation-based components, inbreeding on recent generations was more harmful than inbreeding on more distant generations for yield traits. When \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{PED}$$\end{document}FPED was split into new and ancestral components, based on whether alleles were identical-by-descent for the first time or not, new inbreeding was more harmful than ancestral inbreeding, especially for yield traits. For example, a 1% increase in new inbreeding was associated with a 2.42 kg (SE = 0.41) decrease in 305-day fat yield, compared to a 0.03 kg (SE = 0.71) increase for ancestral inbreeding. There were no clear differences between effects of long ROH (recent inbreeding) and short ROH (ancient inbreeding).

Conclusions

Inbreeding depression was observed for yield, fertility and udder health traits. For yield traits and based on pedigree, inbreeding on recent generations was more harmful than inbreeding on distant generations and there was evidence of purging. Across all traits, long and short ROH contributed to inbreeding depression. In future work, inbreeding depression and purging should be assessed in more detail at the genomic level, using higher density information and genomic time series.

The impact of genomic selection on genetic diversity and genetic gain in three French dairy cattle breeds

Background

In France, implementation of genomic evaluations in dairy cattle breeds started in 2009 and this has modified the breeding schemes drastically. In this context, the goal of our study was to understand the impact of genomic selection on the genetic diversity of bulls from three French dairy cattle breeds born between 2005 and 2015 (Montbéliarde, Normande and Holstein) and the factors that are involved.

Methods

We compared annual genetic gains, inbreeding rates based on runs of homozygosity (ROH) and pedigree data, and mean ROH length within breeds, before and after the implementation of genomic selection.

Results

Genomic selection induced an increase in mean annual genetic gains of 50, 71 and 33% for Montbéliarde, Normande and Holstein bulls, respectively, and in parallel, the generation intervals were reduced by a factor of 1.7, 1.9 and 2, respectively. We found no significant change in inbreeding rate for the two national breeds, Montbéliarde and Normande, and a significant increase in inbreeding rate for the Holstein international breed, which is now as high as 0.55% per year based on ROH and 0.49% per year based on pedigree data (equivalent to a rate of 1.36 and 1.39% per generation, respectively). The mean ROH length was longer for bulls from the Holstein breed than for those from the other two breeds.

Conclusions

With the implementation of genomic selection, the annual genetic gain increased for bulls from the three major French dairy cattle breeds. At the same time, the annual loss of genetic diversity increased for Holstein bulls, possibly because of the massive use of a few elite bulls in this breed, but not for Montbéliarde and Normande bulls. The increase in mean ROH length in Holstein may reflect the occurrence of recent inbreeding. New strategies in breeding schemes, such as female donor stations and embryo transfer, and recent implementation of genomic evaluations in small regional breeds should be studied carefully in order to ensure the sustainability of breeding schemes in the future.

Efficient use of genomic information for sustainable genetic improvement in small cattle populations

In this study, we compared genetic gain, genetic variation, and the efficiency of converting variation into gain under different genomic selection scenarios with truncation or optimum contribution selection in a small dairy population by simulation. Breeding programs have to maximize genetic gain but also ensure sustainability by maintaining genetic variation. Numerous studies have shown that genomic selection increases genetic gain. Although genomic selection is a well-established method, small populations still struggle with choosing the most sustainable strategy to adopt this type of selection. We developed a simulator of a dairy population and simulated a model after the Slovenian Brown Swiss population with ∼10,500 cows. We compared different truncation selection scenarios by varying (1) the method of sire selection and their use on cows or bull-dams, and (2) selection intensity and the number of years a sire is in use. Furthermore, we compared different optimum contribution selection scenarios with optimization of sire selection and their usage. We compared scenarios in terms of genetic gain, selection accuracy, generation interval, genetic and genic variance, rate of coancestry, effective population size, and conversion efficiency. The results showed that early use of genomically tested sires increased genetic gain compared with progeny testing, as expected from changes in selection accuracy and generation interval. A faster turnover of sires from year to year and higher intensity increased the genetic gain even further but increased the loss of genetic variation per year. Although maximizing intensity gave the lowest conversion efficiency, faster turnover of sires gave an intermediate conversion efficiency. The largest conversion efficiency was achieved with the simultaneous use of genomically and progeny-tested sires that were used over several years. Compared with truncation selection, optimizing sire selection and their usage increased the conversion efficiency by achieving either comparable genetic gain for a smaller loss of genetic variation or higher genetic gain for a comparable loss of genetic variation. Our results will help breeding organizations implement sustainable genomic selection.

Genetic improvement of canine hip dysplasia through sire selection across countries

Breeding against canine hip dysplasia (HD) may benefit from the importation of foreign sires. When foreign sires are evaluated on a different HD scale, this may diminish the efficacy. Using stochastic simulations, we evaluated genetic change and inbreeding levels for different scenarios of importing sires with high genetic merit for HD. Population size and genetic parameters (e.g. heritability, accuracy of selection, genetic correlation) were based on actual data for HD in Golden retrievers and Labrador retrievers in the UK and Sweden. For countries with different HD scales and an estimated breeding value (EBV) evaluation in place, the importation was useful if imported sires had EBV rankings in the top 50% and if genetic correlations between EBV systems were above 0.85. When importing sires with EBV rankings in the top 10%, moderate accuracies of EBVs (>0.40) and moderately strong genetic correlations (>0.70) were needed. Selection against HD without the importation of sires may increase inbreeding levels, while the importation of sires can decrease inbreeding levels. For national genetic evaluation and selection programmes, importing sires with high genetic merit can be an effective breeding strategy, but care is needed to estimate reliable EBVs.

Value of the Dutch Holstein Friesian germplasm collection to increase genetic variability and improve genetic merit

National gene bank collections for Holstein Friesian (HF) dairy cattle were set up in the 1990s. In this study, we assessed the value of bulls from the Dutch HF germplasm collection, also known as cryobank bulls, to increase genetic variability and improve genetic merit in the current bull population (bulls born in 2010-2015). Genetic variability was defined as 1 minus the mean genomic similarity (SIM_SNP) or as 1 minus the mean pedigree-based kinship (f_PED). Genetic merit was defined as the mean estimated breeding value for the total merit index or for 1 of 3 subindices (yield, fertility, and udder health). Using optimal contribution selection, we minimized relatedness (maximized variability) or maximized genetic merit at restricted levels of relatedness. We compared breeding schemes with only bulls from 2010 to 2015 with schemes in which cryobank bulls were also included. When we minimized relatedness, inclusion of genotyped cryobank bulls decreased mean SIM_SNP by 0.7% and inclusion of both genotyped and nongenotyped cryobank bulls decreased mean f_PED by 2.6% (in absolute terms). When we maximized merit at restricted levels of relatedness, inclusion of cryobank bulls provided additional merit at any level of mean SIM_SNP or mean f_PED except for the total merit index at high levels of mean SIM_SNP. Additional merit from cryobank bulls depended on (1) the relative emphasis on genetic variability and (2) the selection criterion. Additional merit was higher when more emphasis was put on genetic variability. For fertility, for example, it was 1.74 SD at a mean SIM_SNP restriction of 64.5% and 0.37 SD at a mean SIM_SNP restriction of 67.5%. Additional merit was low to nonexistent for the total merit index and higher for the subindices, especially for fertility. At a mean SIM_SNP of 64.5%, for example, it was 0.60 SD for the total merit index and 1.74 SD for fertility. In conclusion, Dutch HF cryobank bulls can be used to increase genetic variability and improve genetic merit in the current population, although their value is very limited when selecting for the current total merit index. Anticipating changes in the breeding goal in the future, the germplasm collection is a valuable resource for commercial breeding populations.

Genome-Wide Characterization of Selection Signatures and Runs of Homozygosity in Ugandan Goat Breeds

Both natural and artificial selection are among the main driving forces shaping genetic variation across the genome of livestock species. Selection typically leaves signatures in the genome, which are often characterized by high genetic differentiation across breeds and/or a strong reduction in genetic diversity in regions associated with traits under intense selection pressure. In this study, we evaluated selection signatures and genomic inbreeding coefficients, FROH, based on runs of homozygosity (ROH), in six Ugandan goat breeds: Boer (n = 13), and the indigenous breeds Karamojong (n = 15), Kigezi (n = 29), Mubende (n = 29), Small East African (n = 29), and Sebei (n = 29). After genotyping quality control, 45,294 autosomal single nucleotide polymorphisms (SNPs) remained for further analyses. A total of 394 and 6 breed-specific putative selection signatures were identified across all breeds, based on marker-specific fixation index (FST-values) and haplotype differentiation (hapFLK), respectively. These regions were enriched with genes involved in signaling pathways associated directly or indirectly with environmental adaptation, such as immune response (e.g., IL10RB and IL23A), growth and fatty acid composition (e.g., FGF9 and IGF1), and thermo-tolerance (e.g., MTOR and MAPK3). The study revealed little overlap between breeds in genomic regions under selection and generally did not display the typical classic selection signatures as expected due to the complex nature of the traits. In the Boer breed, candidate genes associated with production traits, such as body size and growth (e.g., GJB2 and GJA3) were also identified. Furthermore, analysis of ROH in indigenous goat breeds showed very low levels of genomic inbreeding (with the mean FROH per breed ranging from 0.8% to 2.4%), as compared to higher inbreeding in Boer (mean FROH = 13.8%). Short ROH were more frequent than long ROH, except in Karamojong, providing insight in the developmental history of these goat breeds. This study provides insights into the effects of long-term selection in Boer and indigenous Ugandan goat breeds, which are relevant for implementation of breeding programs and conservation of genetic resources, as well as their sustainable use and management.