Sustainable dairy cattle selection in the genomic era

The role of interleukin-10 receptor alpha (IL10Rα) in Mycobacterium avium subsp. paratuberculosis infection of a mammary epithelial cell line

BACKGROUND

Johne's disease is a chronic wasting disease caused by the bacterium Mycobacterium avium subspecies paratuberculosis (MAP). Johne's disease is highly contagious and MAP infection in dairy cattle can eventually lead to death. With no available treatment for Johne's disease, genetic selection and improvements in management practices could help reduce its prevalence. In a previous study, the gene coding interleukin-10 receptor subunit alpha (IL10Rα) was associated with Johne's disease in dairy cattle. Our objective was to determine how IL10Rα affects the pathogenesis of MAP by examining the effect of a live MAP challenge on a mammary epithelial cell line (MAC-T) that had IL10Rα knocked out using CRISPR/cas9. The wild type and the IL10Rα knockout MAC-T cell lines were exposed to live MAP bacteria for 72 h. Thereafter, mRNA was extracted from infected and uninfected cells. Differentially expressed genes were compared between the wild type and the IL10Rα knockout cell lines. Gene ontology was performed based on the differentially expressed genes to determine which biological pathways were involved.

RESULTS

Immune system processes pathways were targeted to determine the effect of IL10Rα on the response to MAP infection. There was a difference in immune response between the wild type and IL10Rα knockout MAC-T cell lines, and less difference in immune response between infected and not infected IL10Rα knockout MAC-T cells, indicating IL10Rα plays an important role in the progression of MAP infection. Additionally, these comparisons allowed us to identify other genes involved in inflammation-mediated chemokine and cytokine signalling, interleukin signalling and toll-like receptor pathways.

CONCLUSIONS

Identifying differentially expressed genes in wild type and ILR10α knockout MAC-T cells infected with live MAP bacteria provided further evidence that IL10Rα contributes to mounting an immune response to MAP infection and allowed us to identify additional potential candidate genes involved in this process. We found there was a complex immune response during MAP infection that is controlled by many genes.

Association of Variants in Innate Immune Genes TLR4 and TLR5 with Reproductive and Milk Production Traits in Czech Simmental Cattle

Bovine genes TLR4 and TLR5, which encode antibacterial toll-like receptors, were screened for polymorphisms in Czech Red Pied (Czech Simmental) cattle to identify variants associated with reproduction, udder health, and milk production traits. Variants were discovered by hybrid resequencing of 164 bulls using HiSeq X-Ten and PacBio technologies and then individually genotyped. Nominal p-values < 0.05 for associations were detected in 18 combinations between 14 polymorphisms and 15 traits using one-way analysis of variance (ANOVA). The TLR4 variants g.610C>T (rs43578094) and g.10310T>G (rs8193072) in reference AC000135.1 were strictly associated with the index of early reproductive disorders and maternal calving ease, respectively, at false discovery rate (FDR) < 0.05. A highly permissive false discovery rate cutoff of 0.6 separated seventeen combinations in both genes comprising eight positives. In the case of the TLR4 variant g.9422T>C (rs8193060), indications were obtained for the association with as many as four reproductive traits: incidence of cystic ovaries, early reproductive disorders, calving ease, and production longevity. The permissive FDR interpretation for the TLR5 data indicated associations with cyst incidence and early reproduction disorders with maternal calving ease. Moreover, three TLR5 polymorphisms correlated with milk production traits. The discrepancy of the observed associations with the predicted impacts of the SNPs on protein function points to the role of haplotypes. Nevertheless, this question should be resolved on a larger scale. The observed associations are endorsed by independent evidence from the published functional roles in other species and by the published QTL mapping data.

Combined single-step evaluation of functional longevity of dairy cows including correlated traits

BACKGROUND

For years, multiple trait genetic evaluations have been used to increase the accuracy of estimated breeding values (EBV) using information from correlated traits. In France, accurate approximations of multiple trait evaluations were implemented for traits that are described by different models by combining the results of univariate best linear unbiased prediction (BLUP) evaluations. Functional longevity (FL) is the trait that has most benefited from this approach. Currently, with many single-step (SS) evaluations, only univariate FL evaluations can be run. The aim of this study was to implement a "combined" SS (CSS) evaluation that extends the "combined" BLUP evaluation to obtain more accurate genomic (G) EBV for FL when information from five correlated traits (somatic cell score, clinical mastitis, conception rate for heifers and cows, and udder depth) is added.

RESULTS

GEBV obtained from univariate SS (USS) evaluations and from a CSS evaluation were compared. The correlations between these GEBV showed the benefits of including information from correlated traits. Indeed, a CSS evaluation run without any performances on FL showed that the indirect information from correlated traits to evaluate FL was substantial. USS and CSS evaluations that mimic SS evaluations with data available in 2016 were compared. For each evaluation separately, the GEBV were sorted and then split into 10 consecutive groups (deciles). Survival curves were calculated for each group, based on the observed productive life of these cows as known in 2021. Regardless of their genotyping status, the worst group of heifers based on their GEBV in 2016 was well identified in the CSS evaluation and they had a substantially shorter herd life, while those in the best heifer group had a longer herd life. The gaps between groups were more important for the genotyped than the ungenotyped heifers, which indicates better prediction of future survival.

CONCLUSIONS

A CSS evaluation is an efficient tool to improve FL. It allows a proper combination of information on functional traits that influence culling. In contrast, because of the strong selection intensity on young bulls for functional traits, the benefit of such a "combined" evaluation of functional traits is more modest for these males.

Influence of dairy farmers' knowledge on their attitudes towards breeding tools and genomic selection

Understanding farmers' attitudes towards traits is critical for developing appropriate breeding goals for dairy production. In response to a research gap in regards to the influence of farmers' knowledge of breeding tools, this study aimed to determine the effect of farmers' knowledge on their attitudes towards the use of breeding tools and traits in typical family-owned farms in Slovenia. An online questionnaire was sent to dairy farmers affiliated with Slovenian breeding associations, and 256 dairy farmers responded. The analysis was conducted in three steps. First, the basic response patterns according to the farmers' knowledge level were determined using latent class analysis. Second, farmers' attitudes towards breeding tools were assessed by 15 statements using principal component analysis. Finally, we were interested in the relationship between farmers' attitudes and knowledge about selection. The results showed that farmers had more knowledge about the benefits of genomic selection, followed by general knowledge about breeding values and the definition of genomic selection, and they had the least knowledge about the reference population. Farmers with more knowledge were statistically significantly more likely than farmers with less knowledge to have higher education, be younger, have a larger herd size, have higher milk production per cow, have the intent to increase herd size and milk quantity, and use genomically tested bulls. No significant relationship was found between belonging to a specific knowledge class and the main breed in the herd, the farmer's gender, production system, or farming in less-favoured areas. The results also show that farmers basically agree that they need written recorded performance data about a bull/cow to know exactly how good the animal is, that the genetic merit (breeding value) of bulls/cows adds to the performance of their progeny, that it is very important to maintain the breed characteristics of bulls/cows, that cooperation in being able to compare animals with other farmers is essential for improving herd performance, and that the possibilities of selecting dairy cows with genomic selection and monogenetic traits must be fully exploited, indicating a positive attitude towards genomic selection. The level of knowledge was shown to influence attitudes towards various aspects of breeding. It was found that the higher the level of knowledge, the more positive the attitude towards genetic and genomic selection, and the more negative the attitude towards traditional selection.

Evolutionary pressures rendered by animal husbandry practices for avian influenza viruses to adapt to humans

Commercial poultry operations produce and crowd billions of birds every year, which is a source of inexpensive animal protein. Commercial poultry is intensely bred for desirable production traits, and currently presents very low variability at the major histocompatibility complex. This situation dampens the advantages conferred by the MHC’s high genetic variability, and crowding generates immunosuppressive stress. We address the proteins of influenza A viruses directly and indirectly involved in host specificities. We discuss how mutants with increased virulence and/or altered host specificity may arise if few class I alleles are the sole selective pressure on avian viruses circulating in immunocompromised poultry. This hypothesis is testable with peptidomics of MHC ligands. Breeding strategies for commercial poultry can easily and inexpensively include high variability of MHC as a trait of interest, to help save billions of dollars as a disease burden caused by influenza and decrease the risk of selecting highly virulent strains.

Genomic Prediction of Complex Traits in Animal Breeding with Long Breeding History, the Dairy Cattle Case

In accordance with the infinitesimal model for quantitative traits, a very large number of genes affect nearly all economic traits. In only two cases has the causative polymorphism been determined for genes affecting economic traits in dairy cattle. Most current methods for genomic evaluation are based on the "two-step" method. Genetic evaluations are computed by the individual animal model, and functions of the evaluations of progeny-tested sires are the dependent variable for estimation of marker effects. With the adoption of genomic evaluation in 2008, annual rates of genetic gain in the US increased from ∼50-100% for yield traits and from threefold to fourfold for lowly heritable traits, including female fertility, herd-life and somatic cell concentration. Gradual elimination of the progeny test scheme has led to a reduction in the number of sires with daughter records and less genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and "environmentally friendly" production. Genetic variance for economic traits is maintained by increase in frequency of rare alleles, new mutations, and changes in selection goals and management.

Toward Genome-Based Selection in Asian Seabass: What Can We Learn From Other Food Fishes and Farm Animals?

Due to the steadily increasing need for seafood and the plateauing output of fisheries, more fish need to be produced by aquaculture production. In parallel with the improvement of farming methods, elite food fish lines with superior traits for production must be generated by selection programs that utilize cutting-edge tools of genomics. The purpose of this review is to provide a historical overview and status report of a selection program performed on a catadromous predator, the Asian seabass (Lates calcarifer, Bloch 1790) that can change its sex during its lifetime. We describe the practices of wet lab, farm and lab in detail by focusing onto the foundations and achievements of the program. In addition to the approaches used for selection, our review also provides an inventory of genetic/genomic platforms and technologies developed to (i) provide current and future support for the selection process; and (ii) improve our understanding of the biology of the species. Approaches used for the improvement of terrestrial farm animals are used as examples and references, as those processes are far ahead of the ones used in aquaculture and thus they might help those working on fish to select the best possible options and avoid potential pitfalls.

Genetic Diversity and Population Genetic Structure of a Guzerá (Bos indicus) Meta-Population

The Brazilian Guzerá population originated from a few founders introduced from India. These animals adapted well to the harsh environments in Brazil, were selected for beef, milk, or dual-purpose (beef and milk), and were extensively used to produce crossbred animals. Here, the impact of these historical events with regard to the population structure and genetic diversity in a Guzerá meta-population was evaluated. DNA samples of 744 animals (one dairy, nine dual-purpose, and five beef herds) were genotyped for 21 microsatellite loci. Ho, He, PIC, Fis, Fit, and Fst estimates were obtained considering either farms or lineages as subpopulations. Mean Ho (0.73) and PIC (0.75) suggest that genetic diversity was efficiently conserved. Fit, Fis and Fst values (95% CI) pointed to a low fixation index, and large genetic diversity: Fit (Farms = 0.021-0.100; lineages = 0.021-0.100), Fis (Farms = -0.007-0.076; lineages = -0.014-0.070), and Fst (Farms = 0.0237-0.032; lineages = 0.029-0.038). The dual-purpose herds/selection lines are the most uniform subpopulation, while the beef one preserved larger amounts of genetic diversity among herds. In addition, the dairy herd showed to be genetically distant from other herds. Taken together, these results suggest that this Guzerá meta-population has high genetic diversity, a low degree of population subdivision, and a low inbreeding level.

Factors affecting accuracy of estimated effective number of chromosome segments for numerically small breeds

For numerically small breeds, obtaining a sufficiently large breed-specific reference population for genomic prediction is challenging or simply not possible, but may be overcome by adding individuals from another breed. To prioritize among available breeds, the effective number of chromosome segments (Me ) can be used as an indicator of relatedness between individuals from different breeds. The Me is also an important parameter in determining the accuracy of genomic prediction. The Me can be estimated both within a population and between two populations or breeds, as the reciprocal of the variance of genomic relationships. However, the threshold for number of individuals needed to accurately estimate within or between populations Me is currently unknown. It is also unknown if a discrepancy in number of genotyped individuals in two breeds affects the estimates of Me between populations. In this study, we conducted a simulation that mimics current domestic cattle populations in order to investigate how estimated Me is affected by number of genotyped individuals, single-nucleotide polymorphism (SNP) density and pedigree availability. Our results show that a small sample of 10 genotyped individuals may result in substantial over or underestimation of Me . While estimates of within population Me were hardly affected by SNP density, between population Me values were highly dependent on the number of available SNPs, with higher SNP densities being able to detect more independent chromosome segments. When subtracting pedigree from genomic relationships before computing Me , estimates of within population Me were three to four times higher than estimates with genotypes only; however, between Me estimates remained the same. For accurate estimation of within and between population Me , at least 50 individuals should be genotyped per population. Estimates of within Me were highly affected by whether pedigree was used or not. For within Me , even the smallest SNP density (~11k) resulted in accurate representation of family relationships in the population; however, for between Me , many more markers are needed to capture all independent segments.

Symposium review: How to implement genomic selection

Genomic selection was adopted very quickly in the 10 yr after first implementation, and breeders continue to find new uses for genomic testing. Breeding values with higher reliability earlier in life are estimated by combining DNA genotypes for many thousands of loci using existing identification, pedigree, and phenotype databases for millions of animals. Quality control for both new and previous data is greatly improved by comparing genomic and pedigree relationships to correct parent-progeny conflicts and discover many additional ancestors. Many quantitative trait loci and gene tests have been added to previous assays that used only evenly spaced, highly polymorphic markers. Imputation now combines genotypes from many assays of differing marker densities. Prediction models have gradually advanced from normal or Bayesian distributions within trait and breed to single-step, multitrait, or other more complex models, such as multibreed models that may be needed for crossbred prediction. Genomic selection was initially applied to males to predict progeny performance but is now widely applied to females or even embryos to predict their own later performance. The initial focus on additive merit has expanded to include mating programs, genomic inbreeding, and recessive alleles. Many producers now use DNA testing to decide which heifers should be inseminated with elite dairy, beef, or sex-sorted semen, which should be embryo donors or recipients, or which should be sold or kept for breeding. Because some of these decisions are expensive to delay, predictions are now provided weekly instead of every few months. Predictions from international genomic databases are often more accurate and cost-effective than those from within-country databases that were previously designed for progeny testing unless local breeds, conditions, or traits differ greatly from the larger database. Selection indexes include many new traits, often with lower heritability or requiring large initial investments to obtain phenotypes, which provide further incentive to cooperate internationally. The genomic prediction methods developed for dairy cattle are now applied widely to many animal, human, and plant populations and could be applied to many more.

Association of TLR gene variants in a Czech Red Pied cattle population with reproductive traits

The bovine genes TLR1, TLR2 and TLR6, which encode Toll-like receptors, key components of the innate immune system, were screened for polymorphisms in Czech Red Pied (Czech Simmental) cattle, and the different variants present in the population were tested for association with reproductive and fitness traits. Diversity was investigated in a group of 164 bulls using hybrid resequencing of pooled amplicons with PacBio technology and of pooled genomic DNA using HiSeq X-Ten technology. The validated single nucleotide polymorphisms (SNPs) were genotyped in individual animals using the primer extension technique. The association of genotypic classes of 16 polymorphisms with six phenotypic traits were estimated with one-way analysis of variance (ANOVA) and with restricted maximum likelihood (REML) algorithm. The evaluated traits included the incidence of cystic ovaries, index of early reproductive disorders, paternal and maternal indicators of calving ease, production longevity and calf vitality index. The estimated breeding values were used for combined trait quantification. Early traits, namely, cystic ovaries and early reproductive disorders, were not associated with any of the tested polymorphisms according to the general ANOVA test. By contrast, five variants of all three genes were associated with calving ease, both paternal and maternal. The production longevity correlated with two variants of TLR1 and the calf vitality index correlated with the 1044 T > C (rs68268249) polymorphism in TLR2. The false discovery rate (FDR) according to Benjamini-Hochberg was favourable for the calving ease trait (0.221) and maternal calving ease (0.214), which allows to consider the observed associations real, regardless of the error arising from the multiple comparisons. These results were supported by REML only partially, probably in view of the additivity assumption. Two mechanisms of action on calving are conceivable, either via infection resistance or via the involvement of TLR2 in signalling in the myometrium. The known formation of heterodimers by the TLR1, -2 and -6 products might be responsible for the shared pattern of action in these genes. The association of the calf vitality index with TLR2 variation might reflect the increased role of infections in calves compared to adult animals.

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.

Potential of TLR-gene diversity in Czech indigenous cattle for resistance breeding as revealed by hybrid sequencing

A production herd of Czech Simmental cattle (Czech Red Pied, CRP), the conserved subpopulation of this breed, and the ancient local breed Czech Red cattle (CR) were screened for diversity in the antibacterial toll-like receptors (TLRs), which are members of the innate immune system. Polymerase chain reaction (PCR) amplicons of TLR1, TLR2, TLR4, TLR5, and TLR6 from pooled DNA samples were sequenced with PacBio technology, with 3- 5 ×  coverage per gene per animal. To increase the reliability of variant detection, the gDNA pools were sequenced in parallel with the Illumina X-ten platform at low coverage ( 60 × per gene). The diversity in conserved CRP and CR was similar to the diversity in conserved and modern CRP, representing 76.4 % and 70.9 % of its variants, respectively. Sixty-eight (54.4 %) polymorphisms in the five TLR genes were shared by the two breeds, whereas 38 (30.4 %) were specific to the production herd of CRP; 4 (3.2 %) were specific to the broad CRP population; 7 (5.6 %) were present in both conserved populations; 5 (4.0 %) were present solely for the conserved CRP; and 3 (2.4 %) were restricted to CR. Consequently, gene pool erosion related to intensive breeding did not occur in Czech Simmental cattle. Similarly, no considerable consequences were found from known bottlenecks in the history of Czech Red cattle. On the other hand, the distinctness of the conserved populations and their potential for resistance breeding were only moderate. This relationship might be transferable to other non-abundant historical cattle breeds that are conserved as genetic resources. The estimates of polymorphism impact using Variant Effect Predictor and SIFT software tools allowed for the identification of candidate single-nucleotide polymorphisms (SNPs) for association studies related to infection resistance and targeted breeding. Knowledge of TLR-gene diversity present in Czech Simmental populations may aid in the potential transfer of variant characteristics from other breeds.

Genotyping strategies of selection candidates in livestock breeding programmes

Benefits of genomic selection (GS) in livestock breeding operations are well known particularly where traits are sex-limited, hard to measure, have a low heritability and/or measured later in life. Sheep and beef breeders have a higher cost:benefit ratio for GS compared to dairy. Therefore, strategies for genotyping selection candidates should be explored to maximize the economic benefit of GS. The aim of the paper was to investigate, via simulation, the additional genetic gain achieved by selecting proportions of male selection candidates to be genotyped via truncation selection. A two-trait selection index was used that contained an easy and early-in-life measurement (such as post-weaning weight) as well as a hard-to-measure trait (such as intra-muscular fat). We also evaluated the optimal proportion of female selection candidates to be genotyped in breeding programmes using natural mating and/or artificial insemination (NatAI), multiple ovulation and embryo transfer (MOET) or juvenile in vitro fertilization and embryo transfer (JIVET). The final aim of the project was to investigate the total dollars spent to increase the genetic merit by one genetic standard deviation (SD) using GS and/or reproductive technologies. For NatAI and MOET breeding programmes, females were selected to have progeny by 2 years of age, while 1-month-old females were required for JIVET. Genomic testing the top 20% of male selection candidates achieved 80% of the maximum benefit from GS when selection of male candidates prior to genomic testing had an accuracy of 0.36, while 54% needed to be tested to get the same benefit when the prior selection accuracy was 0.11. To achieve 80% of the maximum benefit in female, selection required 66%, 47% and 56% of female selection candidates to be genotyped in NatAI, MOET and JIVET breeding programmes, respectively. While JIVET and MOET breeding programmes achieved the highest annual genetic gain, genotyping male selection candidates provides the most economical way to increase rates of genetic gain facilitated by genomic testing.

Identification of genome regions determining semen quality in Holstein-Friesian bulls using information theory

Use of information theory can be an alternative statistical approach to detect genome regions and candidate genes that are associated with livestock traits. The aim of this study was to verify the validity of the SNPs effects on some semen quality variables of bulls using entropy analysis. Records from 288 Holstein-Friesian bulls from one AI station were included. The following semen quality variables were analyzed: CASA kinematic variables of sperm (total motility, average path velocity, straight line velocity, curvilinear velocity, amplitude of lateral head displacement, beat cross frequency, straightness, linearity), sperm membrane integrity (plazmolema, mitochondrial function), sperm ATP content. Molecular data included 48,192 SNPs. After filtering (call rate = 0.95 and MAF = 0.05), 34,794 SNPs were included in the entropy analysis. The entropy and conditional entropy were estimated for each SNP. Conditional entropy quantifies the remaining uncertainty about values of the variable with the knowledge of SNP. The most informative SNPs for each variable were determined. The computations were performed using the R statistical package. A majority of the loci had relatively small contributions. The most informative SNPs for all variables were mainly located on chromosomes: 3, 4, 5 and 16. The results from the study indicate that important genome regions and candidate genes that determine semen quality variables in bulls are located on a number of chromosomes. Some detected clusters of SNPs were located in RNA (U6 and 5S_rRNA) for all the variables for which analysis occurred. Associations between PARK2 as well GALNT13 genes and some semen characteristics were also detected.

Invited review: Learning from the future-A vision for dairy farms and cows in 2067

The world's population will reach 10.4 billion in 2067, with 81% residing in Africa or Asia. Arable land available for food production will decrease to 0.15 ha per person. Temperature will increase in tropical and temperate zones, especially in the Northern Hemisphere, and this will push growing seasons and dairy farming away from arid areas and into more northern latitudes. Dairy consumption will increase because it provides essential nutrients more efficiently than many other agricultural systems. Dairy farming will become modernized in developing countries and milk production per cow will increase, doubling in countries with advanced dairying systems. Profitability of dairy farms will be the key to their sustainability. Genetic improvements will include emphasis on the coding genome and associated noncoding epigenome of cattle, and on microbiomes of dairy cattle and farmsteads. Farm sizes will increase and there will be greater lateral integration of housing and management of dairy cattle of different ages and production stages. Integrated sensors, robotics, and automation will replace much of the manual labor on farms. Managing the epigenome and microbiome will become part of routine herd management. Innovations in dairy facilities will improve the health of cows and permit expression of natural behaviors. Herds will be viewed as superorganisms, and studies of herds as observational units will lead to improvements in productivity, health, and well-being of dairy cattle, and improve the agroecology and sustainability of dairy farms. Dairy farmers in 2067 will meet the world's needs for essential nutrients by adopting technologies and practices that provide improved cow health and longevity, profitable dairy farms, and sustainable agriculture.

Factors affecting reproductive performance in dromedary camel herds in Saudi Arabia

A survey of 7122 dromedary camels in 115 herds in Saudi Arabia was used to estimate the effects of herd size (HZ; < 25 vs. 25-49 vs. 50-100 vs. > 100 camels), herder/camels ratio (H/C; 1:< 25 vs. 1:25-50 vs. 1:> 50), manager experience (ME; < 5 vs. 5-10 vs. > 10 years), male/females ratio (M/F), housing system (HS; free vs. closed vs. mixed), length of the breeding season (winter vs. winter and spring vs. fall, winter and spring), age at first mating (3 vs. > 3 years), and time of mating after parturition (≤ 3 vs. > 3 months) and their interactions on the overall pregnancy rate. Barren females of these herds (n = 886) were examined for the causes of infertility. Results showed that herds with H/C of 1:< 25 had higher overall pregnancy rate (95.29%) than herds with H/C of 1:25-50 (79.84%) and those with H/C of 1:> 50 (72.79%) (p = 0.003). Herds having ME of > 10 years revealed greater overall pregnancy rate (94.89%) than herds with ME of 5-10 years (80.54%) and those with ME of < 5 years (72.5%) (p = 0.001). There were significant interactions between H/C × HZ (p = 0.003), H/C × HS (p = 0.006), and ME × HS (p = 0.02). The overall pregnancy rate did not significantly differ between herds bred females by age of 3 years and those bred females by age > 3 years and in females bred within 3 months after parturition and in those bred after 3 months. The mean calving interval was shorter (p = 0.008) in camels mated within 3 months of parturition (15.25 ± 2.8 months) than in those mated after that time (24.33 ± 6.5 months). Clinical endometritis, ovarian hydrobursitis, and vaginal adhesions were the common clinical findings in barren females. Thus, efforts to reduce the age at first mating and the interval after calving, increase the number of herders/camels, and control reproductive disorders could improve the reproductive performance and quality of camel herds in Saudi Arabia.

Which Individuals To Choose To Update the Reference Population? Minimizing the Loss of Genetic Diversity in Animal Genomic Selection Programs

Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a potential loss of genetic diversity. Existing methods to conserve genetic diversity depend mostly on the choice of the breeding individuals. In this study, we propose a modification of the reference population composition to mitigate diversity loss. Since the high cost of phenotyping is the limiting factor for GS, our findings are of major economic interest. This study aims to answer the following questions: how would decisions on the reference population affect the breeding population, and how to best select individuals to update the reference population and balance maximizing genetic gain and minimizing loss of genetic diversity? We investigated three updating strategies for the reference population: random, truncation, and optimal contribution (OC) strategies. OC maximizes genetic merit for a fixed loss of genetic diversity. A French Montbéliarde dairy cattle population with 50K SNP chip genotypes and simulations over 10 generations were used to compare these different strategies using milk production as the trait of interest. Candidates were selected to update the reference population. Prediction bias and both genetic merit and diversity were measured. Changes in the reference population composition slightly affected the breeding population. Optimal contribution strategy appeared to be an acceptable compromise to maintain both genetic gain and diversity in the reference and the breeding populations.

Invited review: A perspective on the future of genomic selection in dairy cattle

Genomic evaluation has been successfully implemented in the United States, Canada, Great Britain, Ireland, New Zealand, Australia, France, the Netherlands, Germany, and the Scandinavian countries. Adoption of this technology in the major dairy producing countries has led to significant changes in the worldwide dairy industry. Gradual elimination of the progeny test system has led to a reduction in the number of sires with daughter records and fewer genetic ties between years. As genotyping costs decrease, the number of cows genotyped will continue to increase, and these records will become the basic data used to compute genomic evaluations, most likely via application of "single-step" methodologies. Although genomic selection has been successful in increasing rates of genetic gain, we still know very little about the genetic architecture of quantitative variation. Apparently, a very large number of genes affect nearly all economic traits, in accordance with the infinitesimal model for quantitative traits. Less emphasis in selection goals will be placed on milk production traits, and more on health, reproduction, and efficiency traits and on environmentally friendly production with reduced waste and gas emission. Genetic variance for economic traits is maintained by the increase in frequency of rare alleles, new mutations, and changes in selection goals and management. Thus, it is unlikely that a selection plateau will be reached in the near future.

Diversity of the TLR4 Immunity Receptor in Czech Native Cattle Breeds Revealed Using the Pacific Biosciences Sequencing Platform

The allelic variants of immunity genes in historical breeds likely reflect local infection pressure and therefore represent a reservoir for breeding. Screening to determine the diversity of the Toll-like receptor gene TLR4 was conducted in two conserved cattle breeds: Czech Red and Czech Red Pied. High-throughput sequencing of pooled PCR amplicons using the PacBio platform revealed polymorphisms, which were subsequently confirmed via genotyping techniques. Eight SNPs found in coding and adjacent regions were grouped into 18 haplotypes, representing a significant portion of the known diversity in the global breed panel and presumably exceeding diversity in production populations. Notably, the ancient Czech Red breed appeared to possess greater haplotype diversity than the Czech Red Pied breed, a Simmental variant, although the haplotype frequencies might have been distorted by significant crossbreeding and bottlenecks in the history of Czech Red cattle. The differences in haplotype frequencies validated the phenotypic distinctness of the local breeds. Due to the availability of Czech Red Pied production herds, the effect of intensive breeding on TLR diversity can be evaluated in this model. The advantages of the Pacific Biosciences technology for the resequencing of long PCR fragments with subsequent direct phasing were independently validated.

Optimization of a genomic breeding program for a moderately sized dairy cattle population

Although it now standard practice to genotype thousands of female calves, genotyping of bull calves is generally limited to progeny of elite cows. In addition to genotyping costs, increasing the pool of candidate sires requires purchase, isolation, and identification of calves until selection decisions are made. We economically optimized via simulation a genomic breeding program for a population of approximately 120,000 milk-recorded cows, corresponding to the Israeli Holstein population. All 30,000 heifers and 60,000 older cows of parities 1 to 3 were potential bull dams. Animals were assumed to have genetic evaluations for a trait with heritability of 0.25 derived by an animal model evaluation of the population. Only bull calves were assumed to be genotyped. A pseudo-phenotype corresponding to each animal's genetic evaluation was generated, consisting of the animal's genetic value plus a residual with variance set to obtain the assumed reliability for each group of animals. Between 4 and 15 bulls and between 200 and 27,000 cows with the highest pseudo-phenotypes were selected as candidate bull parents. For all progeny of the founder animals, genetic values were simulated as the mean of the parental values plus a Mendelian sampling effect with variance of 0.5. A probability of 0.3 for a healthy bull calf per mating, and a genomic reliability of 0.43 were assumed. The 40 bull calves with the highest genomic evaluations were selected for general service for 1 yr. Costs included genotyping of candidate bulls and their dams, purchase of the calves from the farmers, and identification. Costs of raising culled calves were partially recovered by resale for beef. Annual costs were estimated as $10,922 + $305 × candidate bulls. Nominal profit per cow per genetic standard deviation was $106. Economic optimum with a discount rate of 5%, first returns after 4 yr, and a profit horizon of 15 yr were obtained with genotyping 1,620 to 1,750 calves for all numbers of bull sires. However, 95% of the optimal profit can be achieved with only 240 to 300 calves. The higher reliabilities achieved through addition of genomic information to the selection process contribute not only in obtaining higher genetic gain, but also in obtaining higher absolute profits. In addition, the optimal profits are obtained for a lower number of calves born in each generation. Inbreeding, as allowed within genomic selection for the Israeli herd, had virtually no effect on genetic gain or on profits, when compared with the case of exclusion of all matings that generate inbreeding. Annual response to selection ranged from 0.35 to 0.4 genetic standard deviation for 4 to 15 bull sires, as compared with 0.25 to 0.3 for a comparable half-sib design without genomic selection.

Genomic evaluation of regional dairy cattle breeds in single-breed and multibreed contexts

An important prerequisite for high prediction accuracy in genomic prediction is the availability of a large training population, which allows accurate marker effect estimation. This requirement is not fulfilled in case of regional breeds with a limited number of breeding animals. We assessed the efficiency of the current French routine genomic evaluation procedure in four regional breeds (Abondance, Tarentaise, French Simmental and Vosgienne) as well as the potential benefits when the training populations consisting of males and females of these breeds are merged to form a multibreed training population. Genomic evaluation was 5-11% more accurate than a pedigree-based BLUP in three of the four breeds, while the numerically smallest breed showed a < 1% increase in accuracy. Multibreed genomic evaluation was beneficial for two breeds (Abondance and French Simmental) with maximum gains of 5 and 8% in correlation coefficients between yield deviations and genomic estimated breeding values, when compared to the single-breed genomic evaluation results. Inflation of genomic evaluation of young candidates was also reduced. Our results indicate that genomic selection can be effective in regional breeds as well. Here, we provide empirical evidence proving that genetic distance between breeds is only one of the factors affecting the efficiency of multibreed genomic evaluation.

Review: Opportunities and challenges for small populations of dairy cattle in the era of genomics

In modern dairy cattle breeding, genomic breeding programs have the potential to increase efficiency and genetic gain. At the same time, the requirements and the availability of genotypes and phenotypes present a challenge. The set-up of a large enough reference population for genomic prediction is problematic for numerically small breeds but also for hard to measure traits. The first part of this study is a review of the current literature on strategies to overcome the lack of reference data. One solution is the use of combined reference populations from different breeds, different countries, or different research populations. Results reveal that the level of relationship between the merged populations is the most important factor. Compiling closely related populations facilitates the accurate estimation of marker effects and thus results in high accuracies of genomic prediction. Consequently, mixed reference populations of the same breed, but from different countries are more promising than combining different breeds, especially if those are more distantly related. The use of female reference information has the potential to enlarge the reference population size. Including females is advisable for small populations and difficult traits, and maybe combined with genotyping females and imputing those that are un-genotyped. The efficient use of imputation for un-genotyped individuals requires a set of genotyped related animals and well-considered selection strategies which animals to choose for genotyping and phenotyping. Small populations have to find ways to derive additional advantages from the cost-intensive establishment of genomic breeding schemes. Possible solutions may be the use of genomic information for inbreeding control, parentage verification, within-herd selection, adjusted mating plans or conservation strategies. The second part of the paper deals with the issue of high-quality phenotypes against the background of new, difficult and hard to measure traits. The use of contracted herds for phenotyping is recommended, as additional traits, when compared to standard traits used in dairy cattle breeding can be measured at set moments in time. This can be undertaken even for the recording of health traits, thus resulting in complete contemporary groups for health traits. Future traits to be recorded and used in genomic breeding programs, at least partly will be traits for which traditional selection based on widespread phenotyping is not possible. Enabling phenotyping of sufficient numbers to enable genomic selection will rely on cooperation between scientists from different disciplines and may require multidisciplinary approaches.