Hossein Jorjani

Genotype by Environment Interaction in Nordic Dairy Cattle Studied Using Reaction Norms

Genotype by environment interaction for production and fertility was studied by use of a reaction norm model. Milk recording data, comprising 927 929 records, were analysed to predict reaction norms for young bulls of the Nordic Red dairy breeds. Random regressions were estimated for each bull, regressing phenotypic values of daughters on herd environment. The phenotypic measures were 305 days kg protein production and days open in first lactation. The herd environment was defined as the herd-year average of protein production and days open, respectively. Heritability of protein production and days open and genetic correlation between the two traits were estimated as functions of the herd environment. The results showed that the genetic parameters change over environments, which are measured on a continuous scale across countries. Grouping of observations is avoided and thereby the problem of genetic connectedness between groups or countries may be avoided. Although significant genetic variation for the slope of the reaction norm was found, there was little reranking of sires, except between extreme environments. More appropriate models and methods need to be developed for further studies of genetic variation in reaction norms.

A genome-wide association study using international breeding-evaluation data identifies major loci affecting production traits and stature in the Brown Swiss cattle breed.

BackgroundThe genome-wide association study (GWAS) is a useful approach to identify genes affecting economically important traits in dairy cattle. Here, we report the results from a GWAS based on high-density SNP genotype data and estimated breeding values for nine production, fertility, body conformation, udder health and workability traits in the Brown Swiss cattle population that is part of the international genomic evaluation program.ResultGWASs were performed using 50 k SNP chip data and deregressed estimated breeding values (DEBVs) for nine traits from between 2061 and 5043 bulls that were part of the international genomic evaluation program coordinated by Interbull Center. The nine traits were milk yield (MY), fat yield (FY), protein yield (PY), lactating cow’s ability to recycle after calving (CRC), angularity (ANG), body depth (BDE), stature (STA), milk somatic cell score (SCS) and milk speed (MSP). Analyses were performed using a linear mixed model correcting for population confounding. A total of 74 SNPs were detected to be genome-wide significantly associated with one or several of the nine analyzed traits. The strongest signal was identified on chromosome 25 for milk production traits, stature and body depth. Other signals were on chromosome 11 for angularity, chromosome 24 for somatic cell score, and chromosome 6 for milking speed. Some signals overlapped with earlier reported QTL for similar traits in other cattle populations and were located close to interesting candidate genes worthy of further investigations.ConclusionsOur study shows that international genetic evaluation data is a useful resource for identifying genetic factors influencing complex traits in livestock. Several genome wide significant association signals could be identified in the Brown Swiss population, including a major signal on BTA25. Our findings report several associations and plausible candidate genes that deserve further exploration in other populations and molecular dissection to explore the potential economic impact and the genetic mechanisms underlying these production traits in cattle.

Reaction norms for protein yield and days open in Swedish red and white dairy cattle in relation to various environmental variables

Various environmental variables were used in analysis of genotype by environment interaction (GxE) for first lactation protein yield and days open in Swedish Red and White dairy cattle. The environmental variables described the herd level of production and fertility, herd size, geographic position, and weather conditions of the herds. Fixed effects of the environmental variables were analysed using a fixed regression sire model. All studied environmental variables, except the average rainfall during summer, had significant effect on both protein yield and days open. Possible effects of GxE were evaluated using random regression of protein yield and days open on the environmental variables. GxE was indicated between protein yield and herd level of production, protein yield and herd size, and days open and herd level of fertility. Correlations between the traits expressed at average and deviating levels of the environment were high indicating that GxE did not result in reranking of sires within the range of environments found in Sweden.

Effects of a national genomic preselection on the international genetic evaluations

Genomic preselection of young bulls is now widely implemented in dairy breeding schemes, especially in the Holstein breed. However, if this step is not accounted for in genetic evaluation models, the national breeding values of bulls retained by a genomic preselection and of their progeny are estimated with bias. It follows that countries participating in international genetic evaluations will provide a selected and possibly biased set of data to the Interbull Centre (Swedish University of Agricultural Sciences, Uppsala, Sweden). The objective of the study was to show evidence of bias at the international level due to a genomic preselection step in national breeding schemes. The consequence of a genomic preselection for the international evaluations (i.e., using selected and biased national estimated breeding values) was simulated using actual national estimated breeding values as a proxy for genomically enhanced breeding values. Data were provided for 3 countries with a large population of Holstein bulls. International breeding values from simulated scenarios were compared with international breeding values using all available data, assumed to be complete and unbiased. Bias was measured among young bulls retained by a genomic preselection and their contemporaries in other countries. The results were analyzed by traits measured within each country and by country of origin of the young bulls. It turned out that sending preselected data, though based on genomic information, created bias in international evaluations, penalizing young bulls from the country sending the incorrect data. It also had an effect on the young bulls from the other countries. Sending biased data further affected the quality of international evaluations. This study underlines the importance of accounting for genomic preselection at the national level first. Moreover, submitting all available data appeared essential to maintain the quality of the international genetic evaluations after implementation of a genomic preselection step.

Application of a multiple-trait, multiple-country genetic evaluation model for female fertility traits

The need to implement a method that can handle multiple traits per country in international genetic evaluations is evident. Today, many countries have implemented multiple-trait national genetic evaluations and they may expect to have their traits simultaneously analyzed in international genetic evaluations. Traits from the same country are residually correlated and the method currently in use, single-trait multiple across-country evaluation (ST-MACE), cannot handle nonzero residual correlations. Therefore, multiple-trait, multiple across-country evaluation (MT-MACE) was proposed to handle several traits from the same country simultaneously. To test the robustness of MT-MACE on real data, female fertility was chosen as a complex trait with low heritability. Data from 7 Holstein populations, 3 with 2 traits and 4 with 1 trait, were used. The differences in the estimated genetic correlations by MT-MACE and the single ST-MACE analysis (average absolute deviation of 0.064) were due to the bias of considering several traits from the same country in the ST-MACE analysis. However, the differences between the estimated genetic correlations by MT-MACE and multiple ST-MACE analyses avoiding more than one trait per country in each analysis (average absolute deviation of 0.066) were due to the lack of analysis of the correlated traits from the same country together and using the reported within-country genetic correlations. Applying MT-MACE resulted in reliability gain in international genetic evaluations, which was different from trait to trait and from bull to bull. The average reliability gain by MT-MACE over ST-MACE was 3.0 points for domestic bulls and 6.3 points for foreign bulls. Even countries with 1 trait benefited from the joint analysis of traits from the 2-trait countries. Another superiority of MT-MACE over ST-MACE is that the bulls that do not have national genetic evaluation for some traits from multiple trait countries will receive international genetic evaluations for those traits. Rank correlations were high between ST-MACE and MT-MACE when considering all bulls. However, the situation was different for the top 100 bulls. Simultaneous analysis of traits from the same country affected bull ranks, especially for top 100 bulls. Multi-trait MACE is a recommendable and robust method for international genetic evaluations and is appropriate for handling multiple traits per country, which can increase the reliability of international genetic evaluations.

Genetic studies of assortative mating—a simulation study. III. Assortative mating in selected populations

Effects of 25 generations of positive assortative mating, random mating and negative assortative mating in simulated selected populations of various effective size (N e = 40, 100, 200) were compared. The trait under consideration was controlled by either 100 or 2500 loci. Positive assortative mating produced the highest cumulative selection response (11.61–13.24 σ P ), followed by random mating (11.00–12.48 σ P ) and negative assortative mating (10.88–11.98 σ P ). The differences between the various mating systems were highly significant (P < 0.001) after the second generation and depended on the covariance due to linkage disequilibrium (C 1) and varying rates of fixation of the favourable alleles, leading to different genic variance (V a). Positive assortative mating first caused C 1 to increase to maximum values equal to 10.8% of the base population genetic variance (V A) when the trait was controlled by 100 loci and then to decline gradually. A faster rate of change in gene frequency caused V ato decre...

Evaluation of genetic variation in the international Brown Swiss population.

The international Brown Swiss cattle population pedigree was studied to measure genetic variations and to identify the most influential animals. Twenty-two countries provided pedigree information on 71 497 Brown Swiss bulls used for artificial insemination (AI). The total number of animals with the pedigree is 181 094. The mean inbreeding coefficient for the pedigree population was 0.77%. There was, in most cases, an increase in the mean inbreeding coefficient, with the highest value at 2.89% during the last 5-year period (2000 to 2004). The mean average relatedness for the pedigree population was 1.1%. The effective population size in 2004 was 204. There was notable variation between average generation intervals for the four parental pathways. The longest average generation interval, at 8.73 years, was observed in the sire-son pathway. The average generation interval for the whole population was 6.53 years. Most genetically influential individuals were sires. The highest contributing founder was a sire with a 3.22% contribution, and the highest contributing founder dam made a contribution of 1.75%. The effective number of founders and the effective number of ancestors were 141 and 88, respectively. The study showed that genetic variation within the pedigree population has been decreasing over recent years. Increasing the number of AI bulls with a low individual coefficient of inbreeding could help to maintain a good level of genetic variation in the Brown Swiss population.

Scandinavian Selection and Crossbreeding Experiment with Laying Hens: V. Specialised Compared with Index Selection for Two Genetically Antagonistic Traits in Laying Hens

Abstract Egg number (EN42) and egg weight (EW42) in the period between age at first egg and 42 weeks of age (P1) were used as the criteria of selection for ten generations in two specialised lines. Two other lines were selected for an index of egg number and egg weight for four generations, and thereafter these two lines were combined with egg mass in P1 (EM42) as the criterion of selection. A random mated control population was also kept throughout the experimental period. Selection for EN42, EW42 and EM42 resulted in a direct cumulative response in generation 10 of about 30 eggs, 16 g of egg weight and more than 1000 g of egg mass in the respective lines in P1. Correlated results in the residual period were generally in good agreement with expectations. Crosses of the two specialised lines were compared with index/egg mass line, and it was concluded that there is an optimum value for the number of generations that the process of crossing the specialised lines is worthwhile, i.e. generation six in our ex...

Genetic studies of assortative mating—a simulation study. I. Characteristics of the Control Populations

Design of control populations to be used in the simulation studies of assortative mating is discussed. In order to be useful for 25 generations a control population should satisfy the following requirements: (i) phenotypic correlation of mates, r P, close to zero; (ii) negligible amount of random drift; and (iii) large number of loci controlling the trait under consideration. It was concluded that under the assumptions of the design used in the present study the number of animals to produce a negligible amount of random drift (200 mating pairs) is much smaller than the number of animals necessary for r p to be sufficiently close to zero to exclude unconscious assortative mating (400 mating pairs). The minimum number of loci required allowing the trait to show a sufficiently large amount of genetic variation even in long‐term selection studies depends, among other things, on the selection intensity and the number of generations involved. In more intensely selected populations more loci are required. In lon...

A practical approach to detect ancestral haplotypes in livestock populations

BackgroundThe effects of different evolutionary forces are expected to lead to the conservation, over many generations, of particular genomic regions (haplotypes) due to the development of linkage disequilibrium (LD). The detection and identification of early (ancestral) haplotypes can be used to clarify the evolutionary dynamics of different populations as well as identify selection signatures and genomic regions of interest to be used both in conservation and breeding programs. The aims of this study were to develop a simple procedure to identify ancestral haplotypes segregating across several generations both within and between populations with genetic links based on whole-genome scanning. This procedure was tested with simulated and then applied to real data from different genotyped populations of Spanish, Fleckvieh, Simmental and Brown-Swiss cattle.ResultsThe identification of ancestral haplotypes has shown coincident patterns of selection across different breeds, allowing the detection of common regions of interest on different bovine chromosomes and mirroring the evolutionary dynamics of the studied populations. These regions, mainly located on chromosomes BTA5, BTA6, BTA7 and BTA21 are related with certain animal traits such as coat colour and milk protein and fat content.ConclusionIn agreement with previous studies, the detection of ancestral haplotypes provides useful information for the development and comparison of breeding and conservation programs both through the identification of selection signatures and other regions of interest, and as indicator of the general genetic status of the populations.