Determination of quantitative trait nucleotides by concordance analysis between quantitative trait loci and marker genotypes of US Holsteins.

Experimental designs that exploit family information can provide substantial predictive power in quantitative trait nucleotide discovery projects. Concordance between quantitative trait locus genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects segregating in the US Holstein population with probabilities of <10-20 to accept the null hypotheses of no segregating gene affecting the trait within the chromosomal segment. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome; 471 Holstein bulls had a complete genome sequence, including 64 of the grandsires. Complete concordance was obtained only for stature on chromosome 14 and daughter pregnancy rate on chromosome 18. For each quantitative trait locus, effects of the 30 polymorphisms with highest concordance scores for the analyzed trait were computed by stepwise regression for predicted transmitting abilities of 26,750 bulls with progeny test and imputed genotypes. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: complete or almost complete concordance, nominal significance of the polymorphism effect after correction for all other polymorphisms, and marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. An intronic variant marker on chromosome 5 at 93,945,738 bp explained 7% of variance for fat percentage and 74% of total multiple-marker regression variance but was concordant for only 24 of 30 families. The missense polymorphism Phe279Tyr in GHR at 31,909,478 bp on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage on chromosome 14, 12 additional missense polymorphisms were found that had almost complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The only polymorphism found likely to improve predictive power for genomic evaluation of dairy cattle was on chromosome 15; that polymorphism had a frequency of 0.45 for the allele with economically positive effects on all production traits.

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.

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.

Genetic and phenotypic analysis of daily Israeli Holstein milk, fat, and protein production as determined by a real-time milk analyzer.

The objective was to test the hypothesis that more frequent but less accurately analyzed milk components may give a more representative measure of a cow's total lactation production. Daily records for milk production and fat and protein concentration collected by the AfiLab recording system (Afimilk, Kibbutz Afikim, Israel) from January 2014 to January 2016 from 47 large kibbutz (communal) herds distributed throughout Israel with a total of 37,486 Israeli Holstein cows were compared with the same statistics derived from monthly test day records derived by Bentley and Foss milk analyzers at the central laboratory of the Israel Cattle Breeders Association. The lactation means for all traits were quite similar for the 2 methods in both parities, except for fat production, which was lower for the daily records. This finding corresponded to fat lactation curves, which showed that daily results were lower with low days in milk (DIM) but almost equal to the monthly results after 125 DIM. Relative to monthly records, daily records overestimated protein percentage before 150 DIM and underestimated protein percentage in the second half of the lactation. The standard deviation for first- and second-parity daily records scored by the monthly and daily system were least similar for fat percentage, but even for this trait the difference was no more than 0.1 percentage points. The standard deviations for complete lactation production were slightly lower for the daily results for all traits but protein production. First-parity heritabilities were higher for lactations computed from daily records for all traits except for protein percentage, but differences were not significant. For daily records, coefficients of determination to predict future milk, fat, and protein lactation production from truncated lactations were greatest and root mean squared errors were least if the mean production from the last 2 weeks before the truncation date was used to estimate future production. Daily first-parity partial lactations for milk, fat, and protein production with <150 DIM predicted future lactation more accurately than corresponding monthly partial lactations. With only 30 DIM, genetic correlations between predicted and actual lactations ranged from 0.73 to 0.79 for milk, fat, and protein production. Real-time daily recording of fat and protein concentration by the daily recording system may be preferable to monthly analysis for herd-management decisions and genetic evaluation. Further study is required to compare the results of individual cows in multiple lactations.

Identification of the sex-determining region in flathead grey mullet (Mugil cephalus).

Elucidation of the sex-determination mechanism in flathead grey mullet (Mugil cephalus) is required to exploit its economic potential by production of genetically determined monosex populations and application of hormonal treatment to parents rather than to the marketed progeny. Our objective was to construct a first-generation linkage map of the M. cephalus in order to identify the sex-determining region and sex-determination system. Deep-sequencing data of a single male was assembled and aligned to the genome of Nile tilapia (Oreochromis niloticus). A total 245 M. cephalus microsatellite markers were designed, spanning the syntenic tilapia genome assembly at intervals of 10 Mb. In the mapping family of full-sib progeny, 156 segregating markers were used to construct a first-generation linkage map of 24 linkage groups (LGs), corresponding to the number of chromosomes. The linkage map spanned approximately 1200 cM with an average inter-marker distance of 10.6 cM. Markers segregating on LG9 in two independent mapping families showed nearly complete concordance with gender (R2  = 0.95). The sex determining locus was fine mapped within an interval of 8.6 cM on LG9. The sex of offspring was determined only by the alleles transmitted from the father, thus indicating an XY sex-determination system.

Comparison of pure Holsteins to crossbred Holsteins with Norwegian Red cattle in first and second generations.

A total of 1922 first generation crossbred cows born between 2005 and 2012 produced by inseminating purebred Israeli Holstein cows with Norwegian Red semen, and 7487 purebred Israeli Holstein cows of the same age in the same 50 herds were analyzed for production, calving traits, fertility, calving diseases, body condition score, abortion rate and survival under intensive commercial management conditions. Holstein cows were higher than crossbreds for 305-day milk, fat and protein production. Differences were 764, 1244, 1231 for kg milk; 23.4, 37.4, 35.6 for kg fat, and 16.7, 29.8, 29.8 for kg protein; for parities 1 through 3. Differences for fat concentration were not significant; while crossbred cows were higher for protein concentration by 0.06% to 0.08%. Differences for somatic cells counts were not significant. Milk production persistency was higher for Holstein cows by 5, 8.3 and 8% in parities 1 through 3. Crossbred cows were higher for conception status by 3.1, 3.6 and 4.7% in parities 1 through 3. Rates of metritis for Holsteins were higher than the crossbred cows by 7.8, 4.6 and 3.4% in parities 1 to 3. Differences for incidence of abortion, dystocia, ketosis and milk fever were not significant. Holstein cows were lower than crossbred cows for body condition score for all three parities, with differences of 0.2 to 0.4 units. Contrary to comparisons in other countries, herd-life was higher for Holsteins by 79 days. A total of 6321 Holstein cows born between 2007 and 2011 were higher than 765 progeny of crossbred cows backcrossed to Israeli Holsteins of the same ages for milk, fat and protein production. Differences were 279, 537, 542 kg milk; 10.5, 17.7, 17.0 kg fat and 6.2, 12.9, 13.2 kg protein for parities 1 through 3. Differences for fat concentration were not significant, while backcross cows were higher for protein percentage by 0.02% to 0.04%. The differences for somatic cell score, conception rate, and calving diseases other than metritis, were not significant. Holstein cows were lower than backcross cows by 1.5% to 2.5% for conception status in parities 1 to 3 and lower for body condition score for parities 1 and 2, with differences in the range of 0.06 to 0.09 units. Culling rates were higher, and herd-life lower for the crossbred cows. The gains obtained in secondary traits for crossbred cows did not compensate for the major reduction in production.

Genetic analysis of calving traits by the multi-trait individual animal model.

Five alternative models were applied for analysis of dystocia and stillbirth in first and second parities. Models 1 and 2 were included only to estimate the parameters required for model 4, and models 3 and 5 are included only as comparisons to the model 4 estimates. Variance components were estimated by multi-trait REML, including cows with valid calving records for both parities. For the effects of sire of calf on first and second parities, variance components were estimated including only calvings with the same sire of calf for both parities. All heritabilities for the cow effect were quite low, but higher for dystocia than for stillbirth and higher in first parity. The sire-of-calf heritabilities were higher than the cow effect heritabilities, except for stillbirth in parity 2. Unlike the effect of cow correlations, all sire of calf correlations were >0.6, and the correlations for the same trait in parities 1 and 2 were >0.9. Thus, a multi-trait analysis should yield a significant gain in accuracy with respect to the sire of calf effects for bulls not mated to virgin heifers. A multi-trait individual animal model algorithm was developed for joint analysis of dystocia and stillbirth in first and second parities. Relationships matrices were included both for the effects of cow and sire of calf. In addition, random herd-year-season and fixed sex of calf effects were included in the model. Records were preadjusted for calving month and age. A total of 899,223 Israeli Holstein cows with first calvings since 1985 were included in the complete analysis. Approximate reliabilities were computed for both sire of cow and sire of calf effects. Correlations between these reliabilities and reliabilities obtained by direct inversion of the coefficient matrix for a sire of cow-sire of calf model were all close to 0.99. Phenotypic trends for cows born from 1983 through 2007 were economically unfavorable for dystocia and favorable for stillbirth in both parities. Genetic trends were economically unfavorable for both dystocia and stillbirth in first parity. First-parity sire of calf trends were unfavorable for dystocia, but favorable for stillbirth. All environmental trends were nearly zero. Regressions of evaluations of the complete analysis on a model including only calvings before 2011 were all >0.8. All evaluations met the Interbull Method 3 criterion for unbiasedness. Model 4, which computed genetic evaluations for all animals for all 4 traits accounting for all known relationships and correlations among the traits, is recommended for routine genetic evaluation of calving traits.

Genomic evaluation of a relatively small dairy cattle population by combination with a larger population.

The objectives were to investigate the accuracy of genomic evaluations obtained for a small dairy cattle population (Israeli Holsteins) via joint evaluation with a larger population (Dutch Holsteins), and to evaluate the use of pedigree data from foreign bulls computed by Interbull without daughter records in Israel. The training population included 4,010 Dutch bulls and 713 Israeli bulls. The validation population included 185 Israeli bulls with daughter records for milk production traits and slightly fewer bulls for the nonproduction traits. Milk, fat, and protein yields, somatic cell score, longevity, female fertility, direct and maternal calving ease, direct and maternal stillbirth, and the Israeli breeding index were analyzed. The genomic prediction model was based on the Bayesian multi-QTL model of Meuwissen and Goddard, where the effects of dense single nucleotide polymorphisms across the whole genome are fitted directly, without the use of haplotypes or identical-by-descent probabilities. Correlations of May 2014 estimated breeding values (EBV14) with genomic EBV (GEBV) were higher than the correlations of EBV14 with parent averages (PA) computed from the June 2009 evaluation for all traits. For the Israel selection index, the difference between EBV14 and GEBV correlation on the one hand and EBV14 and PA computed using Interbull data on the other hand was 15 percentage points. For protein, the difference between the corresponding correlations was 14 percentage points. Generally, correlations of EBV14 with PA based on Israeli EBV only were similar to correlations of EBV14 with PA including Interbull evaluations. Relative to EBV14, milk production traits were biased upwards for both GEBV and PA, but the bias was greater for PA. The Y-intercepts of regressions of EBV14 were significantly different from zero for regression on GEBV for all 3 milk production traits and the Israeli selection index. This was not the case for regression of EBV14 on PA. The regression line intersected with the line of unbiased estimation near the EBV of the bulls with highest values. Because only bulls with high evaluations are of interest for selection, GEBV for these bulls were less biased compared with that of bulls with lower evaluations. The difference in mean EBV14 between bulls born during 2007-2008 selected by GEBV and PA was 65 units. If half of all inseminations are by young bulls, then the annual genetic gain obtained by implementation of genomic evaluation will be 8 units per year (65/8). Because annual gain is currently 107 units, this is a gain of 7%.

Environmental and genetic factors affecting cow survival of Israeli Holsteins.

The objectives were to investigate the effects of various environmental factors that may affect herd-life of Israeli Holsteins, including first-calving age and season, calving ease, number of progeny born, and service sire for first calving in complete and truncated records; and to estimate heritabilities and genetic correlations between herd-life and the other traits included in the Israeli breeding index. The basic data set consisted of 590,869 cows in milk recording herds with first freshening day between 1985 and at least 8 yr before the cut-off date of September 15, 2013. Herd-life was measured as days from first calving to culling. The phenotypic and genetic trends for herd-life were 5.7 and 16.8d/yr. The genetic trend was almost linear, whereas the phenotypic trend showed 4 peaks and 3 valleys. Cows born in February and March had the shortest herd-life, whereas cows born in September had the longest herd-life. Herd-life was maximal with calving age of 23mo, which is 1mo less than the mean calving age, and minimal at 19 and 31mo of calving age. Dystocia and twinning on first-parity calving reduced herd-life by approximately180 and 120d, but the interaction effect increased herd-life by 140d. Heritability for herd-life was 0.14. Despite the fact that the service sire effect was significant in the fixed model analysis, service sire effect accounted for <0.05% of the total variance. In the analysis of 1,431,938 truncated records, the effects of dystocia and twinning rate were very similar but less than 50% of the effects found in the analysis of complete records. Pregnancy at the truncation date increased expected herd-life by 432d. The correlation between actual herd-life and predicted herd-life based on truncated records was 0.44. Genetic correlations between the truncated records and actual herd-life were 0.75 for records truncated after 6mo but approached unity for records truncated after 3 yr. The genetic correlations of herd-life with first-parity milk, fat, and protein production, somatic cell score (SCS), and female fertility were all positive, except for SCS, in which negative values are economically favorable. The highest correlations with herd-life in absolute value were with female fertility and SCS.

Are evaluations on young genotyped animals benefiting from the past generations?

Data sets of US Holsteins, Israeli Holsteins, and pigs from PIC (a Genus company, Hendersonville, TN) were used to evaluate the effect of different numbers of generations on ability to predict genomic breeding values of young genotyped animals. The influence of including only 2 generations of ancestors (A2) or all ancestors (Af) was also investigated. A total of 34,506 US Holsteins, 1,305 Israeli Holsteins, and 5,236 pigs were genotyped. The evaluations were computed by traditional BLUP and single-step genomic BLUP, and computing performance was assessed for the latter method. For the 2 Holstein data sets, coefficients of determination (R(2)) and regression (δ) of deregressed evaluations from a full data set with records up to 2011 on estimated breeding values and genomic estimated breeding values from the truncated data sets were computed. The thresholds for data deletion were set by intervals of 5 yr, based on the average generation interval in dairy cattle. For the PIC data set, correlations between corrected phenotypes and estimated or genomic estimated breeding values were used to evaluate predictive ability on young animals born in 2010 and 2011. The reduced data set contained data up to 2009, and the thresholds were set based on an average generation interval of 3 yr. The number of generations that could be deleted without a reduction in accuracy depended on data structure and trait. For US Holsteins, removing 3 and 4 generations of data did not reduce accuracy of evaluations for final score in Af and A2 scenarios, respectively. For Israeli Holsteins, the accuracies for milk, fat, and protein yields were the highest when only phenotypes recorded in 2000 and later were included and full pedigrees were applied. Of the 135 Israeli bulls with genotypes (validation set) and daughter records only in the complete data set, 38 and 97 were sons of Israeli and foreign bulls, respectively. Although more phenotypic data increased the prediction accuracy for sons of Israeli bulls, the reverse was true for sons of foreign bulls. Also, more phenotypic data caused large inflation of genomic estimated breeding values for sons of foreign bulls, whereas the opposite was true with the deletion of all but the most recent phenotypic data. Results for protein and fat percentage were different from those for milk, fat, and protein yields; however, relatively, the changes in coefficients of determination and regression were smaller for percentage traits. For PIC data set, removing data from up to 5 generations did not erode predictive ability for genotyped animals for the 2 reproductive traits used in validation. Given the data used in this study, truncating old data reduces computation requirements but does not decrease the accuracy. For small populations that include local and imported animals, truncation may be beneficial for one group of animals and detrimental to another group.

Application of the a posteriori granddaughter design to the Holstein genome.

An a posteriori granddaughter design was applied to estimate quantitative trait loci genotypes of sires with many sons in the US Holstein population. The results of this analysis can be used to determine concordance between specific polymorphisms and segregating quantitative trait loci. Determination of the actual polymorphisms responsible for observed genetic variation should increase the accuracy of genomic evaluations and rates of genetic gain. A total of 52 grandsire families, each with ⩾100 genotyped sons with genetic evaluations based on progeny tests, were analyzed for 33 traits (milk, fat and protein yields; fat and protein percentages; somatic cell score (SCS); productive life; daughter pregnancy rate; heifer and cow conception rates; service-sire and daughter calving ease; service-sire and daughter stillbirth rates; 18 conformation traits; and net merit). Of 617 haplotype segments spanning the entire bovine genome and each including ~5×106 bp, 5 cM and 50 genes, 608 autosomal segments were analyzed. A total of 19 335 unique haplotypes were found among the 52 grandsires. There were a total of 133 chromosomal segment-by-trait combinations, for which the nominal probability of significance for the haplotype effect was <10-8, which corresponds to genome-wide significance of <10-4. The number of chromosomal regions that met this criterion by trait ranged from one for rear legs (rear view) to seven for net merit. For each of the putative quantitative trait loci, at least one grandsire family had a within-family contrast with a t-value of >3. Confidence intervals (CIs) were estimated by the nonparametric bootstrap for the largest effect for each of nine traits. The bootstrap distribution generated by 100 samples was bimodal only for net merit, which had the widest 90% CI (eight haplotype segments). This may be due to the fact that net merit is a composite trait. For all other chromosomes, the CI spanned less than a third of the chromosome. The narrowest CI (a single haplotype segment) was found for SCS. It is likely that analysis by more advanced methods could further reduce CIs at least by half. These results can be used as a first step to determine the actual polymorphisms responsible for observed quantitative variation in dairy cattle.

Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses.

Methods for genomic prediction were evaluated for an Israeli Holstein dairy population of 713,686 cows and 1,305 progeny-tested bulls with genotypes. Inclusion of genotypes of 343 elite cows in an evaluation method that considers pedigree, phenotypes, and genotypes simultaneously was also evaluated. Two data sets were available: a complete data set with production records from 1985 through 2011, and a reduced data set with records after 2006 deleted. For each production trait, a multitrait animal model was used to compute traditional genetic evaluations for parities 1 through 3 as separate traits. Evaluations were calculated for the reduced and complete data sets. The evaluations from the reduced data set were used to calculate parent average for validation bulls, which was the benchmark for comparing gain in predictive ability from genomics. Genomic predictions for bulls in 2006 were calculated using a Bayesian regression method (BayesC), genomic BLUP (GBLUP), single-step GBLUP (ssGBLUP), and weighted ssGBLUP (WssGBLUP). Predictions using BayesC and GBLUP were calculated either with or without an index that included parent average. Genomic predictions that included elite cow genotypes were calculated using ssGBLUP and WssGBLUP. Predictive ability was assessed by coefficients of determination (R(2)) and regressions of predictions of 135 validation bulls with no daughters in 2006 on deregressed evaluations of those bulls in 2011. A reduction in R(2) and regression coefficients was observed from parities 1 through 3. Fat and protein yields had the lowest R(2) for all the methods. On average, R(2) was lowest for parent averages, followed by GBLUP, BayesC, ssGBLUP, and WssGBLUP. For some traits, R(2) for direct genomic values from BayesC and GBLUP were lower than those for parent averages. Genomic estimated breeding values using ssGBLUP were the least biased, and this method appears to be a suitable tool for genomic evaluation of a small genotyped population, as it automatically accounts for parental index, allows for inclusion of female genomic information without preadjustments in evaluations, and uses the same model as in traditional evaluations. Weighted ssGBLUP has the potential for higher evaluation accuracy.

Predictive ability of selected subsets of single nucleotide polymorphisms (SNPs) in a moderately sized dairy cattle population.

Several studies have shown that computation of genomic estimated breeding values (GEBV) with accuracies significantly greater than parent average (PA) estimated breeding values (EBVs) requires genotyping of at least several thousand progeny-tested bulls. For all published analyses, GEBV computed from the selected samples of markers have lower or equal accuracy than GEBV derived on the basis of all valid single nucleotide polymorphisms (SNPs). In the current study, we report on four new methods for selection of markers. Milk, fat, protein, somatic cell score, fertility, persistency, herd life and the Israeli selection index were analyzed. The 972 Israeli Holstein bulls genotyped with EBV for milk production traits computed from daughter records in 2012 were assigned into a training set of 844 bulls with progeny test EBV in 2008, and a validation set of 128 young bulls. Numbers of bulls in the two sets varied slightly among the nonproduction traits. In EFF12, SNPs were first selected for each trait based on the effects of each marker on the bulls' 2012 EBV corrected for effective relationships, as determined by the SNP matrix. EFF08 was the same as EFF12, except that the SNPs were selected on the basis of the 2008 EBV. In DIFmax, the SNPs with the greatest differences in allelic frequency between the bulls in the training and validation sets were selected, whereas in DIFmin the SNPs with the smallest differences were selected. For all methods, the numbers of SNPs retained varied over the range of 300 to 6000. For each trait, except fertility, an optimum number of markers between 800 and 5000 was obtained for EFF12, based on the correlation between the GEBV and current EBV of the validation bulls. For all traits, the difference between the correlation of GEBV and current EBV and the correlation of the PA and current EBV was >0.25. EFF08 was inferior to EFF12, and was generally no better than PA EBV. DIFmax always outperformed DIFmin and generally outperformed EFF08 and PA. Furthermore, GEBV based on DIFmax were generally less biased than PA. It is likely that other methods of SNP selection could improve upon these results.

Maternity validation using sire-only BovineSNP50 BeadChip data.

Based on pairwise identity-by-state (IBS) distances and whole-genome SNP data, kinship was investigated in the Israeli Holstein population. A total of 789 bulls, including most of the artificial insemination sires in service since 1987, were genotyped by the BovineSNP50 BeadChip. This sample included up to five generations. For each bull-by-bull combination, three states are possible for each marker: no match, a single match and both alleles match. Summing over all markers, the 932 598 IBS scores (three match frequencies*310 866 bull-by-bull combinations) were visualized using three-dimensional coordinates that corresponded to the frequencies of the three possible states. Results were reduced to two dimensions using the transformations x' = 0.7071(1 + freq1-freq2) and y' = 1.2247freq0. Bull-by-bull pairs were grouped according to their level of kinship, and canonical scores were calculated using discriminant analysis and the x' and y' features. Of the 474 pairs of recorded maternal grandsire-grandson with both individuals genotyped, the probability for 28 pairs to belong to this level of kinship was low (P < 0.05), suggesting an error rate of around 3% per generation in pedigree determination.

Application of a posteriori granddaughter and modified granddaughter designs to determine Holstein haplotype effects.

A posteriori and modified granddaughter designs were applied to determine haplotype effects for Holstein bulls and cows with BovineSNP50 [~50,000 single nucleotide polymorphisms (SNP); Illumina Inc., San Diego, CA] genotypes. The a posteriori granddaughter design was applied to 52 sire families, each with ≥100 genotyped sons with genetic evaluations based on progeny tests. For 33 traits (milk, fat, and protein yields; fat and protein percentages; somatic cell score; productive life; daughter pregnancy rate; heifer and cow conception rates; service-sire and daughter calving ease; service-sire and daughter stillbirth; 18 conformation traits; and net merit), the analysis was applied to the autosomal segment with the SNP with the greatest effect in the genomic evaluation of each trait. All traits except 2 had a within-family haplotype effect. The same design was applied with the genetic evaluations of sons corrected for SNP effects associated with chromosomes besides the one under analysis. The number of within-family contrasts was 166 without adjustment and 211 with adjustment. Of the 52 bulls analyzed, 36 had BovineHD (high density; Illumina Inc.) genotypes that were used to test for concordance between sire quantitative trait loci and SNP genotypes; complete concordance was not obtained for any effects. Of the 31 traits with effects from the a posteriori granddaughter design, 21 were analyzed with the modified granddaughter design. Only sires with a contrast for the a posteriori granddaughter design and ≥200 granddaughters with a record usable for genetic evaluation were included. Calving traits could not be analyzed because individual cow evaluations were not computed. Eight traits had within-family haplotype effects. With respect to milk and fat yields and fat percentage, the results on Bos taurus autosome (BTA) 14 corresponded to the hypothesis that a missense mutation in the diacylglycerol O-acyltransferase 1 (DGAT1) gene is the main causative mutation, although other polymorphisms in that gene also modify fat yield and percentage. The positive allele for protein concentration was less frequent, which indicated that selection on that locus could be effective. Although the results can be used to determine causative polymorphisms for most of the analyzed traits, complete DNA sequencing of most of the analyzed sires probably will be required.

Signatures of contemporary selection in the Israeli Holstein dairy cattle.

Strong selection in the Israeli Holstein dairy cattle population over the last three decades should have left clear signatures of selection. Two experimental approaches were applied to detect evidence of contemporary selection based on the 54K BeadChip genotypes of ~1000 Israeli Holstein bulls: (i) the long-range haplotype test, which searches for structural evidence resulting from selective sweep, and (ii) direct analysis of the changes in haplotypes frequencies over time combined with linkage disequilibrium blocks haplotype-based association analysis. Ten traits were analyzed: the PD07 Israeli selection index, milk, milk fat, % fat, milk protein, % protein, somatic cell score, female fertility, milk production persistency and herd life. The long-range haplotype test detected ~15% of the 3288 haplotypes that showed significant positive frequency trends (P < 0.05) and was significantly correlated with the substitution effects of the haplotypes and the selection intensities for the different traits. Thirty signatures of recent selection, which correspond to both approaches and affect the Israeli PD07 selection index, were identified on 17 of the 29 autosomes. The second experimental approach also was used to estimate the selection intensity of the different traits. The correlation between the selection intensities for the traits analyzed, derived from changes in haplotype frequencies in the population of bulls, and those derived from trait-based analysis of the cow population was 0.93 over all traits. Thus, the changes in haplotypes frequencies in the bulls' population accurately estimate genetic trends in the general cow population and can be used to detect signatures of recent selection.

A simple method for genomic selection of moderately sized dairy cattle populations.

An efficient algorithm for genomic selection of moderately sized populations based on single nucleotide polymorphism chip technology is described. A total of 995 Israeli Holstein bulls with genetic evaluations based on daughter records were genotyped for either the BovineSNP50 BeadChip or the BovineSNP50 v2 BeadChip. Milk, fat, protein, somatic cell score, female fertility, milk production persistency and herd-life were analyzed. The 400 markers with the greatest effects on each trait were first selected based on individual analysis of each marker with the genetic evaluations of the bulls as the dependent variable. The effects of all 400 markers were estimated jointly using a 'cow model,' estimated from the data truncated to exclude lactations with freshening dates after September 2006. Genotype probabilities for each locus were computed for all animals with missing genotypes. In Method I, genetic evaluations were computed by analysis of the truncated data set with the sum of the marker effects subtracted from each record. Genomic estimated breeding values for the young bulls with genotypes, but without daughter records, were then computed as their parent averages combined with the sum of each animal's marker effects. Method II genomic breeding values were computed based on regressions of estimated breeding values of bulls with daughter record on their parent averages, sum of marker effects and birth year. Method II correlations of the current breeding values of young bulls without daughter records in the truncated data set were higher than the correlations of the current breeding values with the parent averages for fat and protein production, persistency and herd-life. Bias of evaluations, estimated as a difference between the mean of current breeding values of the young bulls and their genomic evaluations, was reduced for milk production traits, persistency and herd-life. Bias for milk production traits was slightly negative, as opposed to the positive bias of parent averages. Correlations of Method II with the means of daughter records adjusted for fixed effects were higher than parent averages for fat, protein, fertility, persistency and herd-life. Reducing the number of markers included in the analysis from 400 to 300 did not reduce correlations of genomic breeding values for protein with current breeding values, but did slightly reduce correlations with means of daughter records. Method II has the advantages as compared with the method of VanRaden in that genotypes of cows can be readily incorporated into the Method II analysis, and it is more effective for moderately sized populations.

Linkage and Physical Mapping of Sex Region on LG23 of Nile Tilapia (Oreochromis niloticus).

Evidence supports that sex determination (SD) in tilapia is controlled by major genetic factors that may interact with minor genetic as well as environmental factors, thus implying that SD should be analyzed as a quantitative trait. Quantitative trait loci (QTL) for SD in Oreochromis niloticus were previously detected on linkage groups (LG) 1 and 23. Twenty-one short single repeats (SSR) of >12 TGs and one single nucleotide polymorphism were identified using the unpublished tilapia genome sequence on LG23. All markers showed two segregating alleles in a mapping family that was obtained by a cross between O. niloticus male (XY) and sex-reversed female (ΔXY) yielding 29 females (XX) and 61 males (XY and YY). Interval mapping analysis mapped the QTL peak between SSR markers ARO172 and ARO177 with a maximum F value of 78.7 (P < 7.6 × 10(-14)). Twelve adjacent markers found in this region were homozygous in females and either homozygous for the alternative allele or heterozygous in males. This segment was defined as the sex region (SR). The SR encompasses 1.5 Mbp on a single tilapia scaffold (no. 101) harboring 51 annotated genes. Among 10 candidate genes for SD that were tested for gene expression, anti-Müllerian hormone (Amh), which is located in the center of the SR, showed the highest overexpression in male vs. female embryos at 3 to 7 days postfertilization.

Ovine mitochondrial DNA sequence variation and its association with production and reproduction traits within an Afec-Assaf flock.

Polymorphisms in mitochondrial DNA (mtDNA) protein- and tRNA-coding genes were shown to be associated with various diseases in humans as well as with production and reproduction traits in livestock. Alignment of full length mitochondria sequences from the 5 known ovine haplogroups: HA (n = 3), HB (n = 5), HC (n = 3), HD (n = 2), and HE (n = 2; GenBank accession nos. HE577847-50 and 11 published complete ovine mitochondria sequences) revealed sequence variation in 10 out of the 13 protein coding mtDNA sequences. Twenty-six of the 245 variable sites found in the protein coding sequences represent non-synonymous mutations. Sequence variation was observed also in 8 out of the 22 tRNA mtDNA sequences. On the basis of the mtDNA control region and cytochrome b partial sequences along with information on maternal lineages within an Afec-Assaf flock, 1,126 Afec-Assaf ewes were assigned to mitochondrial haplogroups HA, HB, and HC, with frequencies of 0.43, 0.43, and 0.14, respectively. Analysis of birth weight and growth rate records of lamb (n = 1286) and productivity from 4,993 lambing records revealed no association between mitochondrial haplogroup affiliation and female longevity, lambs perinatal survival rate, birth weight, and daily growth rate of lambs up to 150 d that averaged 1,664 d, 88.3%, 4.5 kg, and 320 g/d, respectively. However, significant (P < 0.0001) differences among the haplogroups were found for prolificacy of ewes, with prolificacies (mean ± SE) of 2.14 ± 0.04, 2.25 ± 0.04, and 2.30 ± 0.06 lamb born/ewe lambing for the HA, HB, and the HC haplogroups, respectively. Our results highlight the ovine mitogenome genetic variation in protein- and tRNA coding genes and suggest that sequence variation in ovine mtDNA is associated with variation in ewe prolificacy.

Differential expression of ruminant ZNF496 variants: Association with quantitative trait locus affecting bovine milk concentration and fertility.

A single nucleotide polymorphism in the intergenic region upstream of the ZNF496 gene on Bos taurus chromosome 7 displayed significant population-wide linkage disequilibrium with milk protein percentage in the Israeli Holstein population. The frequency of the allele associated with increased protein concentration was 10%. This single nucleotide polymorphism was located in the promoter region from which a 10-exon transcript of the bovine and the ovine ZNF496 genes are transcribed. The gene architecture was similar to the mouse ortholog Zkscan17. A 5-exon murine antisense transcript was complementary to the 5' untranslated Zkscan17 region that included a sequence domain conserved between mouse and ruminants, suggesting a regulatory function. In the bovine ZNF496 chromosomal region, segregation of a quantitative trait locus (QTL) for milk protein percentage was confirmed in a daughter design sire family. Concordance was not obtained between QTL status of bulls and any of the polymorphisms in the functional elements of ZNF496. This excludes these variations as the causative polymorphism under the assumption of no epigenetic effect for this locus. However, ZNF496 variants were differentially expressed in bovine ovaries, and only the paternal variant was expressed in liver and kidney in a sheep family with polymorphic ZNF496 sequence. Thus, the search for the mutation underlying the minor QTL allele, which is a top economically favorable allele in Israeli Holstein cattle, may be complicated by the presence of an imprinting center in this QTL confidence interval.