Genome-wide association study of economically important traits in Charolais and Limousin beef cows

Genomic selection has proven effective for advancing genetic gain for key profit traits in dairy cattle production systems. However, its impact to-date on genetic improvement programs for beef cattle has been less effective. Despite this, the technology is thought to be particularly useful for low heritability traits such as those associated with reproductive efficiency. The objective of this study was to identify genetic variants associated with key determinants of reproductive and overall productive efficiency in beef cows. The analysis employed a large dataset derived from the national genetic evaluation program in Ireland for two of the most predominant beef breeds, viz. Charolais (n = 5 244 cows) and Limousin (n = 7 304 cows). Single nucleotide polymorphisms (SNPs) were identified as being statistically significantly associated (adj. P < 0.05) with both reproductive and productive traits for both breed types. However, there was little across breed commonality, with only two SNPs (rs110240246 and rs110344317; adj. P < 0.05) located within the genomic regions of the LCORL and MSTN genes respectively, identified in both Charolais and Limousin populations, associated with traits including carcass weight, cull-cow weight and live-weight. Significant SNPs within the MSTN gene were also associated with both reproduction and production related traits within each breed. Finally, traits including calving difficulty, calf mortality and calving interval were associated with SNPs within genomic regions comprising genes involved in cellular growth and lipid metabolism. Genetic variants identified as associated with both important reproductive efficiency and production related traits from this study warrant further analyses for their potential incorporation into breeding programmes to support the sustainability of beef cattle production.     

Artificial selection and maintenance of genetic variance in the global dairy cow population

Genetic improvement of dairy cows, which has increased the milk yield of cows in the UK by 1200 kg per lactation in 12 years, is an excellent example of the application of quantitative genetics to agriculture. The most important traits of dairy cattle are expressed only in females, but the main opportunity for selection is in males. Despite this, genetic improvement was achieved by the invention of a new statistical methodology, called 'best linear unbiased prediction' to estimate the breeding value of bulls. Intense selection of the best bulls, combined with the worldwide use of these bulls through artificial insemination and frozen semen, has created a global population and caused concern that the genetic variation available in the future will be reduced. Maintenance of genetic variation and long-term genetic gains would be aided by rational payment systems, use of crossbreeding where profitable, inclusion of all economically important traits in the breeding objective, recognition of genotype by environment interactions and the use of selection algorithms that balance estimated breeding value against the average relationship among the selected animals. Fortunately, all of these things are happening to some degree.     

Comparative selection signature analyses identify genomic footprints in Reggiana cattle,the traditional breed of the Parmigiano-Reggiano cheese production system

Reggiana is an autochthonous cattle breed reared mainly in the province of Reggio Emilia, located in the North of Italy. Reggiana cattle (originally a triple-purpose population largely diffused in the North of Italy) are characterised by a typical solid red coat colour. About 2500 cows of this breed are currently registered to its herd book. Reggiana is now considered a dual-purpose breed even if it is almost completely dedicated to the production of a mono-breed branded Protected Designation of Origin Parmigiano-Reggiano cheese, which is the main driver of the sustainable conservation of this local genetic resource. In this study, we provided the first overview of genomic footprints that characterise Reggiana and define the diversity of this local cattle breed. A total of 168 Reggiana sires (all bulls born over 35 years for which semen was available) and other 3321 sires from 3 cosmopolitan breeds (Brown, Holstein and Simmental) were genotyped with the Illumina BovineSNP50 panel. ADMIXTURE analysis suggested that Reggiana breed might have been influenced, at least in part, by the other three breeds included in this study. Selection signatures in the Reggiana genome were identified using three statistical approaches based on allele frequency differences among populations or on properties of haplotypes segregating in the populations (fixation index (F_ST); integrated haplotype score; cross-population extended haplotype homozygosity). We identified several regions under peculiar selection in the Reggiana breed, particularly on bovine chromosome (BTA) 6 in the KIT gene region, that is known to be involved in coat colour pattern distribution, and within the region of the LAP3, NCAPG and LCORL genes, that are associated with stature, conformation and carcass traits. Another already known region that includes the PLAG1 gene (BTA14), associated with conformation traits, showed a selection signature in the Reggiana cattle. On BTA18, a signal of selection included the MC1R gene that causes the red coat colour in cattle. Other selection sweeps were in regions, with high density of quantitative trait loci for milk production traits (on BTA20) and in several other large regions that might have contributed to shape and define the Reggiana genome (on BTA17 and BTA29). All these results, overall, indicate that the Reggiana genome might still contain several signs of its multipurpose and non-specialised utilisation, as already described for other local cattle populations, in addition to footprints derived by its ancestral origin and by its adaptation to the specialised Parmigiano-Reggiano cheese production system.     

Sharing reference data and including cows in the reference population improve genomic predictions in Danish Jersey

Small reference populations limit the accuracy of genomic prediction in numerically small breeds, such like Danish Jersey. The objective of this study was to investigate two approaches to improve genomic prediction by increasing size of reference population in Danish Jersey. The first approach was to include North American Jersey bulls in Danish Jersey reference population. The second was to genotype cows and use them as reference animals. The validation of genomic prediction was carried out on bulls and cows, respectively. In validation on bulls, about 300 Danish bulls (depending on traits) born in 2005 and later were used as validation data, and the reference populations were: (1) about 1050 Danish bulls, (2) about 1050 Danish bulls and about 1150 US bulls. In validation on cows, about 3000 Danish cows from 87 young half-sib families were used as validation data, and the reference populations were: (1) about 1250 Danish bulls, (2) about 1250 Danish bulls and about 1150 US bulls, (3) about 1250 Danish bulls and about 4800 cows, (4) about 1250 Danish bulls, 1150 US bulls and 4800 Danish cows. Genomic best linear unbiased prediction model was used to predict breeding values. De-regressed proofs were used as response variables. In the validation on bulls for eight traits, the joint DK-US bull reference population led to higher reliability of genomic prediction than the DK bull reference population for six traits, but not for fertility and longevity. Averaged over the eight traits, the gain was 3 percentage points. In the validation on cows for six traits (fertility and longevity were not available), the gain from inclusion of US bull in reference population was 6.6 percentage points in average over the six traits, and the gain from inclusion of cows was 8.2 percentage points. However, the gains from cows and US bulls were not accumulative. The total gain of including both US bulls and Danish cows was 10.5 percentage points. The results indicate that sharing reference data and including cows in reference population are efficient approaches to increase reliability of genomic prediction. Therefore, genomic selection is promising for numerically small population.     

Genetic variation in milk urea nitrogen concentration of dairy cattle and its implications for reducing urinary nitrogen excretion

Nitrogen (N) leached into groundwater from urine patches of cattle grazing in situ is an environmental problem in pasture-based dairy industries. One potential mitigation is to breed cattle for lower urinary nitrogen (UN) excretion. Urinary nitrogen is difficult to measure, while milk urea nitrogen concentration (MUN) is relatively easy to measure. For animals fed diets of differing N content in confinement, MUN is moderately heritable and is positively related to UN. However, there is little information on the heritability of MUN, and its relationship with other traits such as milk yield and composition, for animals grazing fresh pasture. Milk urea nitrogen concentration data together with milk yield, fat, protein and lactose composition and somatic cell count was collected from 133 624 Holstein-Friesian (HF), Jersey (J) and HF×J (XBd) cows fed predominantly pasture over three full lactations and one part lactation. Mean MUN was 14.0; and 14.4, 13.2 and 13.9 mg/dl for HF, J and XBd cows, respectively. Estimates of heritability of MUN were 0.22 using a repeatability model that fitted year-of-lactation by month-of-lactation by cow-age with days-in-milk within month-of-lactation and cow-age, and 0.28 using a test-day model analysis with Gibbs sampling methods. Sire breeding values (BVs) ranged from −2.8 to +3.2 indicating that MUN could be changed by selection. The genetic correlation between MUN and percent true protein in milk was −0.22; −0.29 for J cows and −0.16 for HF cows. Should the relationship between MUN and UN observed in dietary manipulation studies hold similarly when MUN is manipulated by genetic selection, UN excretion could be reduced by 6.6 kg/cow per year in one generation of selection using sires with low MUN BVs. Although J cows had lower MUN than HF, total herd UN excretion may be similar for the same fixed feed supply because more J cows are required to utilise the available feed. The close relationship between blood plasma urea N concentration and MUN may enable early selection of bulls to breed progeny that excrete less UN.     

Analysis of genetic correlations between beef traits in young bulls and primiparous cows belonging to the dual-purpose Rendena breed

Selection for beef traits in Italian dual-purpose breeds is often carried out using growth and in vivo conformation recorded on young, performance tested bulls and muscularity traits scored during routinely linear type evaluation on primiparous cows. In this context, the knowledge of the genetic structure of traits obtained in different sexes and at different times is necessary for a proper selection plan. This study aimed to estimate, in the local dual-purpose Rendena breed, the genetic relationships between muscularity linear type traits from primiparous cows, the same traits scored on candidate young bulls, and the performance test traits recorded in candidate young bulls. Type traits included: front (chest and shoulder), back (loins and rump); thigh, buttocks side and rear views (two traits). Performance test traits were: average daily gain; EUROP fleshiness evaluation; and dressing percentage. Muscularity linear type traits were recorded on 11 992 first parity cows, and the muscularity type traits were scored on 957 candidate young bulls. Heritability estimates obtained for muscularity traits were moderate in young bulls (on average 0.326), about 16% higher than in primiparous cows. The average heritability for performance test traits in young bulls resulted 0.342. Moderate to strong genetic correlations were found between performance test and muscularity type traits collected in young bulls (from 0.500 between front (chest and shoulder) and average daily gain to 0.955 between thigh, buttocks side view and in vivo dressing percentage). The genetic relationships obtained between muscularity linear type traits of primiparous cows and performance traits of young bulls were variable (from a null correlation between front (chest and shoulder) and average daily gain to 0.822 between thigh, buttocks rear view and dressing percentage), with an average genetic correlation of 0.532. Generally, the traits measured during performance testing in young bulls were favourably correlated with muscularity traits evaluated on primiparous cows, indicating a common selection pathway.     

A comparison of natural service fertility of yearling and two-year-old bulls on pasture

The natural service fertility of yearling bulls on pasture was compared with that of 2-year-old bulls in a study (2 experiments) which involved a total of 748 composite breed cows over 3 breeding seasons. Other factors such as age of the cows, breed, year effects, and the sequence in which bulls of a particular age were assigned to cows were also evaluated. Pregnancy and calving rates and calving date were used as criteria for assessing fertility. The age of the bull, breed, year, or bull sequence did not significantly affect any of the traits studied. The age of cow was important in all the traits studied, with mature cows (5 years and older at breeding) calving earlier (P < 0.05) than the youngest group (2 years old at breeding) of cows, in both experiments. The pregnancy rate was also lower in the younger cows than in the mature cows in the first experiment. The results suggest that the age range of the cow herd is more important in determining herd fertility than the age of the bull or any of the parameters studied.     

Reproductive behaviour in bulls raised under tropical and subtropical conditions

The present review describes the behavioral characteristics of bulls raised under tropical and subtropical conditions and emphasizes the difficulties associated with adequately monitoring their performance in the field to predict reproductive potential. Most of the information generated for improving our understanding of bull behavior under range conditions has been generated in Bos taurus bulls. The limited information available in Bos indicus indicates that males searching for cows in estrus display different sexual patterns when compared to B. taurus bulls and a poor selection of a sire utilized in range conditions can have an important impact in cattle production. Screening and selecting [cg1] bulls for desirable reproductive traits and high libido is known to improve the reproductive performance of the herd. The reproductive and genetic potential of a bull is influenced by factors such as management, age, nutrition and problems related to the female such as embryonic death and anestrus. However, behavioral characteristics of bulls when detecting and serving cows in estrus is poorly understood.     

Effect of genotyped cows in the reference population on the genomic evaluation of Holstein cattle

This study evaluated the dependence of reliability and prediction bias on the prediction method, the contribution of including animals (bulls or cows), and the genetic relatedness, when including genotyped cows in the progeny-tested bull reference population. We performed genomic evaluation using a Japanese Holstein population, and assessed the accuracy of genomic enhanced breeding value (GEBV) for three production traits and 13 linear conformation traits. A total of 4564 animals for production traits and 4172 animals for conformation traits were genotyped using Illumina BovineSNP50 array. Single- and multi-step methods were compared for predicting GEBV in genotyped bull-only and genotyped bull-cow reference populations. No large differences in realized reliability and regression coefficient were found between the two reference populations; however, a slight difference was found between the two methods for production traits. The accuracy of GEBV determined by single-step method increased slightly when genotyped cows were included in the bull reference population, but decreased slightly by multi-step method. A validation study was used to evaluate the accuracy of GEBV when 800 additional genotyped bulls (POPbull) or cows (POPcow) were included in the base reference population composed of 2000 genotyped bulls. The realized reliabilities of POPbull were higher than those of POPcow for all traits. For the gain of realized reliability over the base reference population, the average ratios of POPbull gain to POPcow gain for production traits and conformation traits were 2.6 and 7.2, respectively, and the ratios depended on heritabilities of the traits. For regression coefficient, no large differences were found between the results for POPbull and POPcow. Another validation study was performed to investigate the effect of genetic relatedness between cows and bulls in the reference and test populations. The effect of genetic relationship among bulls in the reference population was also assessed. The results showed that it is important to account for relatedness among bulls in the reference population. Our studies indicate that the prediction method, the contribution ratio of including animals, and genetic relatedness could affect the prediction accuracy in genomic evaluation of Holstein cattle, when including genotyped cows in the reference population.     

Class I antigens of the bovine major histocompatibility system are weakly associated with variation in faecal worm egg counts in naturally infected cattle

Three bulls selected for high faecal worm egg counts and three bulls selected for low faecal worm egg counts were mated to Africander-Hereford cross cows. Faecal worm egg counts were taken on four occasions from the 132 offspring. Also, each animal was typed for 32 class I antigens of the bovine major histocompatibility system (BoLA). Least squares analysis of variance showed that line, sex and some of the antigens were associated with differences in worm egg output in the faeces. After adjusting for the effects of line and sex, cattle with antigen W9 had about twice as many worm eggs in their faeces as cattle without W9; cattle with antigen CA45 had about half the concentration of faecal worm eggs as cattle without CA45. However, the antigen associations were of borderline significance at the 5% level and more work in additional populations is necessary to confirm these associations.     

Estimation of genetic associations between reproduction and production traits based on a sire and dam line with common ancestry

Genetic parameters for survival, reproduction and production traits were estimated for a sire and dam line, originating from one Large White breed separated more than 25 years ago. The change in parameters due to different selection pressure on reproduction and production traits in both lines was also examined. Data collected between 1990 and 2007 were available for the analysis of reproduction traits in 4713 litters (sire line) and 14836 litters (dam line) and for the production traits in 58329 pigs (sire line) and 108912 pigs (dam line). Genetic parameters were estimated using a Bayesian approach. Average phenotypic differences between lines were substantial with 1.5 more piglets born in the dam line and 1.7 mm less backfat thickness (BF) in the sire line. Based on a multiple trait analysis which included both reproduction and production traits, heritabilities for survival and litter size traits in the sire (or dam) line were estimated at 0.03 ± 0.01 (0.06 ± 0.01) for percentage of stillborn piglets (SB), 0.10 ± 0.03 (0.11 ± 0.01) for total number of piglets born (NBT) and 0.09 ± 0.03 (0.09 ± 0.01) for number of piglets born alive. Heritabilities for production traits were estimated at 0.29 ± 0.01 (0.29 ± 0.01) for average daily gain, 0.50 ± 0.01 (0.42 ± 0.01) for BF and 0.41 ± 0.01 for muscle depth. Selection pressure on litter size in the dam line resulted in a slightly unfavourable correlation for SB-NBT (0.21 ± 0.11), which was only marginally unfavourable in the sire line (0.06 ± 0.24). Selection pressure on BF in the sire line may have resulted in the moderately undesirable correlation with SB (-0.46 ± 0.15), which was not significant in the dam line (-0.08 ± 0.06). Changing the base population in the dam line to animals born since the year 2000 indicated that selection pressure on different traits has altered the heritabilities and correlations of the traits within the line. The undesirable correlations between survival at birth and reproduction traits or production traits were low so that simultaneous improvement of all traits can be achieved. Heritabilities for survival at birth and reproduction traits were low, but genetic variation was substantial and extensive pedigree information can be used to improve the accuracy of breeding values, so that genetic improvement is expected to be efficient.     

Assessing the impact of natural service bulls and genotype by environment interactions on genetic gain and inbreeding in organic dairy cattle genomic breeding programs

The objective of the present study was to compare genetic gain and inbreeding coefficients of dairy cattle in organic breeding program designs by applying stochastic simulations. Evaluated breeding strategies were: (i) selecting bulls from conventional breeding programs, and taking into account genotype by environment (G×E) interactions, (ii) selecting genotyped bulls within the organic environment for artificial insemination (AI) programs and (iii) selecting genotyped natural service bulls within organic herds. The simulated conventional population comprised 148 800 cows from 2976 herds with an average herd size of 50 cows per herd, and 1200 cows were assigned to 60 organic herds. In a young bull program, selection criteria of young bulls in both production systems (conventional and organic) were either ‘conventional’ estimated breeding values (EBV) or genomic estimated breeding values (GEBV) for two traits with low (h²=0.05) and moderate heritability (h²=0.30). GEBV were calculated for different accuracies (r_mg), and G×E interactions were considered by modifying originally simulated true breeding values in the range from r_g=0.5 to 1.0. For both traits (h²=0.05 and 0.30) and r_mg⩾0.8, genomic selection of bulls directly in the organic population and using selected bulls via AI revealed higher genetic gain than selecting young bulls in the larger conventional population based on EBV; also without the existence of G×E interactions. Only for pronounced G×E interactions (r_g=0.5), and for highly accurate GEBV for natural service bulls (r_mg>0.9), results suggests the use of genotyped organic natural service bulls instead of implementing an AI program. Inbreeding coefficients of selected bulls and their offspring were generally lower when basing selection decisions for young bulls on GEBV compared with selection strategies based on pedigree indices.     

Accuracy of genomic breeding values in multi-breed dairy cattle populations

Background

Two key findings from genomic selection experiments are 1) the reference population used must be very large to subsequently predict accurate genomic estimated breeding values (GEBV), and 2) prediction equations derived in one breed do not predict accurate GEBV when applied to other breeds. Both findings are a problem for breeds where the number of individuals in the reference population is limited. A multi-breed reference population is a potential solution, and here we investigate the accuracies of GEBV in Holstein dairy cattle and Jersey dairy cattle when the reference population is single breed or multi-breed. The accuracies were obtained both as a function of elements of the inverse coefficient matrix and from the realised accuracies of GEBV.

Methods

Best linear unbiased prediction with a multi-breed genomic relationship matrix (GBLUP) and two Bayesian methods (BAYESA and BAYES_SSVS) which estimate individual SNP effects were used to predict GEBV for 400 and 77 young Holstein and Jersey bulls respectively, from a reference population of 781 and 287 Holstein and Jersey bulls, respectively. Genotypes of 39,048 SNP markers were used. Phenotypes in the reference population were de-regressed breeding values for production traits. For the GBLUP method, expected accuracies calculated from the diagonal of the inverse of coefficient matrix were compared to realised accuracies.

Results

When GBLUP was used, expected accuracies from a function of elements of the inverse coefficient matrix agreed reasonably well with realised accuracies calculated from the correlation between GEBV and EBV in single breed populations, but not in multi-breed populations. When the Bayesian methods were used, realised accuracies of GEBV were up to 13% higher when the multi-breed reference population was used than when a pure breed reference was used. However no consistent increase in accuracy across traits was obtained.

Conclusion

Predicting genomic breeding values using a genomic relationship matrix is an attractive approach to implement genomic selection as expected accuracies of GEBV can be readily derived. However in multi-breed populations, Bayesian approaches give higher accuracies for some traits. Finally, multi-breed reference populations will be a valuable resource to fine map QTL.     

The value of cows in reference populations for genomic selection of new functional traits

Today, almost all reference populations consist of progeny tested bulls. However, older progeny tested bulls do not have reliable estimated breeding values (EBV) for new traits. Thus, to be able to select for these new traits, it is necessary to build a reference population. We used a deterministic prediction model to test the hypothesis that the value of cows in reference populations depends on the availability of phenotypic records. To test the hypothesis, we investigated different strategies of building a reference population for a new functional trait over a 10-year period. The trait was either recorded on a large scale (30 000 cows per year) or on a small scale (2000 cows per year). For large-scale recording, we compared four scenarios where the reference population consisted of 30 sires; 30 sires and 170 test bulls; 30 sires and 2000 cows; or 30 sires, 2000 cows and 170 test bulls in the first year with measurements of the new functional trait. In addition to varying the make-up of the reference population, we also varied the heritability of the trait (h2 = 0.05 v. 0.15). The results showed that a reference population of test bulls, cows and sires results in the highest accuracy of the direct genomic values (DGV) for a new functional trait, regardless of its heritability. For small-scale recording, we compared two scenarios where the reference population consisted of the 2000 cows with phenotypic records or the 30 sires of these cows in the first year with measurements of the new functional trait. The results showed that a reference population of cows results in the highest accuracy of the DGV whether the heritability is 0.05 or 0.15, because variation is lost when phenotypic data on cows are summarized in EBV of their sires. The main conclusions from this study are: (i) the fewer phenotypic records, the larger effect of including cows in the reference population; (ii) for small-scale recording, the accuracy of the DGV will continue to increase for several years, whereas the increases in the accuracy of the DGV quickly decrease with large-scale recording; (iii) it is possible to achieve accuracies of the DGV that enable selection for new functional traits recorded on a large scale within 3 years from commencement of recording; and (iv) a higher heritability benefits a reference population of cows more than a reference population of bulls.     

Signatures of Diversifying Selection in European Pig Breeds

Following domestication, livestock breeds have experienced intense selection pressures for the development of desirable traits. This has resulted in a large diversity of breeds that display variation in many phenotypic traits, such as coat colour, muscle composition, early maturity, growth rate, body size, reproduction, and behaviour. To better understand the relationship between genomic composition and phenotypic diversity arising from breed development, the genomes of 13 traditional and commercial European pig breeds were scanned for signatures of diversifying selection using the Porcine60K SNP chip, applying a between-population (differentiation) approach. Signatures of diversifying selection between breeds were found in genomic regions associated with traits related to breed standard criteria, such as coat colour and ear morphology. Amino acid differences in the EDNRB gene appear to be associated with one of these signatures, and variation in the KITLG gene may be associated with another. Other selection signals were found in genomic regions including QTLs and genes associated with production traits such as reproduction, growth, and fat deposition. Some selection signatures were associated with regions showing evidence of introgression from Asian breeds. When the European breeds were compared with wild boar, genomic regions with high levels of differentiation harboured genes related to bone formation, growth, and fat deposition.     

Genetic correlations among milk yield,morphology, performance test traits and somatic cells in dual-purpose Rendena breed

Selection in native local breeds needs great carefulness due to the small population size and the risk of inbreeding. Furthermore, most breeds are dual-purpose, and milk and beef attitudes are antagonistic. For preservation purposes functional traits need to be considered. Focusing on the small local Rendena cattle, this study aimed to analyse the genetic correlations among milk, beef and udder health traits and the response to selection predicted under different scenarios. The study considered milk, fat and protein yields (MY), factor scores for udder volume (UV), conformation (UC) and muscularity obtained from type traits scored on primiparous cows, and performance test traits (PT) measured on young bulls at test station: average daily gain, in vivo SEUROP fleshiness, in vivo dressing percentage. Somatic cell score (SCS) was considered as a functional trait, with a possibility of restricting its genetic gain to zero. The study considered 281 497 MY test-day data collected on 16 974 cows, and data from linear type evaluation on 11 992 primiparous cows for factor scores. The PT data were recorded on 1428 young bulls, and SCS obtained from cell counts at milk recording. Bi-trait restricted maximum likelihood animal model analyses were performed to assess genetic parameters. Heritability varied from 0.157 (fat) to 0.442 (dressing percentage). Udder volume and MY resulted positively genetically correlated (average correlation 0.427), whereas the low-negative genetic correlation between MY and UC (−0.141) suggested a negative impact of milk gain on udder form. Beef traits of factor muscularity and PT showed medium-high favourable genetic correlations (from 0.357 to 0.984), excluding a null correlation between daily gain and muscularity. The genetic correlation MY v. muscularity was unfavourable (−0.328 on average), whereas null correlations were found in MY v. PT, apart from fat v. dressing percentage (−0.151). Somatic cell score showed low unfavourable correlations with protein (0.111) and UV (0.092), and favourable correlations with UC (−0.193). Response to selection in different scenarios indicated a good balanced gain for milk and beef when standardized economic weights of 0.66 and 0.34 are given to the two attitudes, and SCS genetic gain is restricted. Current genetic trends (MY and PT increasing, but muscularity lessening) reflect a stronger selection for milk, suggesting a slight progressive change towards a milk conformation. Aiming to preserve the dual-purpose characteristics of a breed, proper breeding policies taking into account the genetic relationships among traits and including functional traits should be applied in local dual-purpose populations.     

A definition of unknown parent groups based on bull usage patterns across herds

In genetic evaluations, the definition of unknown parent groups (UPG) is usually based on time periods, selection path and flows of foreign founders. The definition of UPG may be more complex for populations presenting genetic heterogeneity due to both, large national expansion and coexistence of artificial insemination (AI) and natural service (NS). A UPG definition method accounting for beef bull flows was proposed and applied to the French Charolais cattle population. It assumed that, at a given time period, unknown parents belonged to the same UPG when their progeny were bred in herds that used bulls with similar origins (birth region and reproduction way). Thus, the birth period, region and AI rate of a herd were pointed out to be the three criteria reflecting genetic disparities at the national level in a beef cattle population. To deal with regional genetic disparities, 14 regions were identified using a factorial approach combining principal component analysis and Ward clustering. The selection nucleus of the French cattle population was dispersed over three main breeding areas. Flows of NS bulls were mainly carried out within each breeding area. On the contrary, the use and the selection of AI bulls were based on a national pool of candidates. Within a time period, herds of different regions were clustered together when they used bulls coming from the same origin and with an estimated difference of genetic level lower than 20% of genetic standard deviation (σg) for calf muscle and skeleton scores (SS) at weaning. This led to the definition of 16 UPG of sires, which were validated as robust and relevant in a sire model, meaning numerically stable and corresponding to distinct genetic subpopulations. The UPG genetic levels were estimated for muscle and SS under sire and animal models. Whatever the trait, differences between bull UPG estimates within a time period could reach 0.5 σg across regions. For a given time period, bull UPG estimates for muscle and SS were generally larger by 0.30 to 0.75 σg than those of cows. Including genetic groups in the evaluation model increased the estimated genetic trends by 20% to 30%. It also provoked re-ranking in favor of bulls and cows without pedigree.     

Prospects for improving reproductive performance through genetic selection

Prospects for improving female fertility in dairy cattle using genetic selection are reviewed. Today's high producing cows have shorter estrous cycles, fewer standing events, shorter duration of estrus, and more frequent multiple ovulations. Although high milk production is often implicated as the cause of impaired fertility, the impact of inadequate body condition appears to be greater, as the latter has a significant impact on probability of conception, rate of embryonic loss, and proportion of anestrous animals. Genetic improvement of female fertility can be achieved by indirect selection for longevity or body condition score, or by direct selection for traits such as daughter pregnancy rate. Most leading dairy countries have implemented genetic evaluation systems for female fertility in the past decade, but refinement of these systems to account for hormonal synchronization, differences in the voluntary waiting period, exposure to natural service bulls, and other confounding factors is warranted. Recent work has focused on the development of data collection and genetic evaluation systems that will allow selection of bulls that have daughters that are resistant to common health disorders, including mastitis, lameness, ketosis, displaced abomasum, and metritis. Such systems will allow selection of animals that can remain healthy and fertile while producing large quantities of milk.     

Influence of sire and sire breed (Gyr versus Holstein) on establishment of pregnancy and embryonic loss in lactating Holstein cows during summer heat stress

Heat stress has negative effects on pregnancy rates of lactating dairy cattle. There are genetic differences in tolerance to heat stress; Bos taurus indicus (B. t. indicus) cattle and embryos are more thermotolerant than Bos taurus taurus (B. t. taurus). In the present study, the effects of sire and sire breed on conception and embryonic/fetal loss rates of lactating Holstein cows during the Brazilian summer were determined. In Experiment 1, cows (n=302) were AI after estrus detection or at a fixed-time with semen from one Gyr (B. t. indicus) or one Holstein sire (B. t. taurus). Pregnancy was diagnosed 80 days after AI. In Experiment 2, cows (n=811) were AI with semen from three Gyr and two Holstein sires. Pregnancy was diagnosed at 30-40 and at 60-80 days after AI. Cows diagnosed pregnant at the first examination but non-pregnant at the second were considered as having lost their embryo or fetus. Data were analyzed by logistic regression. The model considered the effect of sire within breed, sire breed, days postpartum, period of lactation, and AI type (AI after estrus versus fixed-time). There was no effect of the AI type, days postpartum or milk production on conception or embryonic loss rates. The use of Gyr bulls increased pregnancy rate when compared to Holstein bulls [9.1% (60/657) versus 5.0% (23/456), respectively, P=0.008; data from Experiments 1 and 2 combined]. Additionally, in Experiment 2, cows inseminated using semen from sire #4 (Gyr) had lower embryonic loss (10%) when compared with other B. t. indicus (35.3% and 40%) or B. t. taurus sires (18.2% and 38.5%, P=0.03). In conclusion, the use of B. t. indicus sires may result in higher conception rates in lactating Holstein cows during summer heat stress. Moreover, sire can affect embryonic loss and selection of bulls according to this criterion may result in higher parturition rates in lactating Holstein cows.     

Behavioral constraints on local adaptation and counter‐gradient variation: Implications for climate change

Resource allocation to growth, reproduction, and body maintenance varies within species along latitudinal gradients. Two hypotheses explaining this variation are local adaptation and counter‐gradient variation. The local adaptation hypothesis proposes that populations are adapted to local environmental conditions and are therefore less adapted to environmental conditions at other locations. The counter‐gradient variation hypothesis proposes that one population out performs others across an environmental gradient because its source location has greater selective pressure than other locations. Our study had two goals. First, we tested the local adaptation and counter‐gradient variation hypotheses by measuring effects of environmental temperature on phenotypic expression of reproductive traits in the burying beetle, Nicrophorus orbicollis Say, from three populations along a latitudinal gradient in a common garden experimental design. Second, we compared patterns of variation to evaluate whether traits covary or whether local adaptation of traits precludes adaptive responses by others. Across a latitudinal range, N. orbicollis exhibits variation in initiating reproduction and brood sizes. Consistent with local adaptation: (a) beetles were less likely to initiate breeding at extreme temperatures, especially when that temperature represents their source range; (b) once beetles initiate reproduction, source populations produce relatively larger broods at temperatures consistent with their local environment. Consistent with counter‐gradient variation, lower latitude populations were more successful at producing offspring at lower temperatures. We found no evidence for adaptive variation in other adult or offspring performance traits. This suite of traits does not appear to coevolve along the latitudinal gradient. Rather, response to selection to breed within a narrow temperature range may preclude selection on other traits. Our study highlights that N. orbicollis uses temperature as an environmental cue to determine whether to initiate reproduction, providing insight into how behavior is modified to avoid costly reproductive attempts. Furthermore, our results suggest a temperature constraint that shapes reproductive behavior.