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.

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.

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.

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.

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.

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%.

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.

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.

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.

Chimaerism detection in bovine twins, triplets and quadruplets using sex chromosome-linked markers.

The phenomenon of chimaerism occurs in the majority of cattle twin pregnancies. The objectives of this study were to develop a powerful diagnostic test for chimaerism in bovine male and female co-twins using X and Y chromosome-linked markers and to determine the extent of chimaerism in twins, triplets and quadruplets. We developed a multiplex PCR set of three polymorphic markers on chromosome X (DIK2865, DIK2283, AGLA257), where the presence of >1 and >2 alleles per marker is sufficient to prove chimaerism in males and females, respectively. In addition, a specific segment on chromosome Y (BOV97M) is included in the set to indicate chimaerism in females. Visualization of chimaeric alleles was best for DNA extracted from blood, fair for DNA from vaginal smears and failed for DNA extracted from hair. The power of chimaerism identification using this set of markers for DNA extracted from blood was calculated as 99% in males and virtually 100% in females. All females and males in heterosexual twins, triplets and quadruplets displayed evidence of a chimaeric allele in at least one and maximum of three of three X chromosome markers analysed. In addition, all females showed the presence of the BOV97M segment and were validated as chimaeric by the standard clinical diagnosis of impaired vaginal length. Quantitative PCR analysis of BOV97M copies in all twins vs. their sires showed a mean ratio of 45-68% in females and 39-49% in males, indicating a substantial symmetrical exchange of cells among all co-twins. The proposed analysis of X and Y chromosome-linked markers is advantageous to previous methods based on Y chromosome sequences only, because it detects chimaerism in both male and female co-twins.

Fine-mapping of a locus on linkage group 23 for sex determination in Nile tilapia (Oreochromis niloticus).

Genetic markers in tilapia species associated with loci affecting sex determination (SD), sex-specific mortality or both were mapped to linkage groups (LG) 1, 2, 3, 6 and 23. The objective of this study was to use these markers to fine-map the locus with the greatest effect on SD in Oreochromis niloticus. Our parental stock, full-sibs of Nile tilapia (Swansea origin), were divided into three groups: (i) untreated, (ii) feminized by diethylstilbestrol and (iii) masculinized by 17α-methyltestosterone. We analysed the first group for association of microsatellite markers representing these five LGs. The strongest association with gender was found on LG23 for marker UNH898 (χ(2) ; P=8.6×10(-5) ). Allele 276 was found almost exclusively in males, and we hypothesized that this allele is a male-associated allele (MAA). Sex-reversed individuals were used for mating experiments with and without the segregating MAA. Mating of individuals lacking the MAA resulted in all-female progeny. Mating of two heterozygotes for MAA gave rise to 81 males and 30 females. Analysis of association between gender and genotypes identified the MAA in 98.6% of males as opposed to 8.0% of females (χ(2) ; P=2.5×10(-18) ). Eight markers that flank UNH898 were genotyped to map the locus on LG23 within a confidence interval of 16-21 cM. Mating of homozygous individuals for MAA is underway for production of all-male populations.

Invited review: quantitative trait nucleotide determination in the era of genomic selection.

Genome-wide association studies based on tens of thousands of single nucleotide polymorphisms have been completed for several dairy cattle populations. Methods have been proposed to directly incorporate genome scan data into breeding programs, chiefly by selection of young sires based on their genotypes for the genetic markers and pedigree without progeny test. Thus, the rate of genetic gain is increased by reduction of the mean generation interval. The methods developed so far for application of genomic selection do not require identification of the actual quantitative trait nucleotides (QTN) responsible for the observed variation of quantitative trait loci (QTL). To date, 2 QTN affecting milk production traits have been detected in dairy cattle: DGAT1 and ABCG2. This review will attempt to address the following questions based on the current state of bovine genomics and statistics. What are the pros and cons for QTN determination? How can data obtained from high-density, genome-wide scans be used most efficiently for QTN determination? Can the genome scan results already available and next-generation sequencing data be used to determine QTN? Should QTN be treated differently than markers at linkage disequilibrium with QTL in genetic evaluation programs? Data obtained by genome-wide association studies can be used to deduce QTL genotypes of sires via application of the a posteriori granddaughter design for concordance testing of putative QTN. This, together with next-generation sequencing technology, will dramatically reduce costs for QTN determination. By complete genome sequencing of 21 sires with many artificial insemination sons, it should be possible to determine concordance for all potential QTN, thus establishing the field of QTNomics.

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.

Paternity validation and estimation of genotyping error rate for the BovineSNP50 BeadChip.

Incorrect paternity assignment in cattle can have a major effect on rates of genetic gain. Of the 576 Israeli Holstein bulls genotyped by the BovineSNP50 BeadChip, there were 204 bulls for which the father was also genotyped. The results of 38 828 valid single nucleotide polymorphisms (SNPs) were used to validate paternity, determine the genotyping error rates and determine criteria enabling deletion of defective SNPs from further analysis. Based on the criterion of >2% conflicts between the genotype of the putative sire and son, paternity was rejected for seven bulls (3.5%). The remaining bulls had fewer conflicts by one or two orders of magnitude. Excluding these seven bulls, all other discrepancies between sire and son genotypes are assumed to be caused by genotyping mistakes. The frequency of discrepancies was >0.07 for nine SNPs, and >0.025 for 81 SNPs. The overall frequency of discrepancies was reduced from 0.00017 to 0.00010 after deletion of these 81 SNPs, and the total expected fraction of genotyping errors was estimated to be 0.05%. Paternity of bulls that are genotyped for genomic selection may be verified or traced against candidate sires at virtually no additional cost.

Development of a 25-plex SNP assay for traceability in cattle.

Single nucleotide polymorphisms (SNPs) are amenable to automation and therefore have become the marker of choice for DNA profiling. SNaPshot, a primer extension-based method, was used to multiplex 25 SNPs that have been previously validated as useful for identity control. Detection of extended products was based on four different fluorochromes and extension primers with oligonucleotide tails of differing lengths, thus controlling the concise length of the entire chromatogram to 81 bases. Allele frequencies for Holstein, Simmental, Limousin, Angus, Charolais and Tux Cattle were estimated and significant positive Pearson-correlation coefficients were obtained among the analysed breeds. The probability that two randomly unrelated individuals would share identical genotypes for all 25 loci varied from 10(-8) to 10(-10) for these breeds. For parentage control, the exclusion power was found to be 99.9% when the genotypes of both putative parents are known. A traceability test of duplicated samples indicated a high genotyping precision of >0.998. This was further corroborated by analysis of 60 cases of parent-sib pairs and trio families. The 25-plex SNaPshot assay is adapted for low- and high-throughput capacity and thus presents an alternative for DNA-based traceability in the major commercial cattle breeds.

Estimation of the number of SNP genetic markers required for parentage verification.

Formulae were developed to compute exclusion probabilities for parentage confirmation for any number of diallelic markers under the assumption that the minor allele frequency (MAF) varied among markers, but has a uniform distribution. Three scenarios were analysed: a progeny with (1) a single putative parent; (2) two putative parents; and (3) one actual parent and one putative parent. Exclusion probabilities were computed for minimum values for the MAFs of 0.1, 0.2 and 0.3, and required either one or at least two conflicts for exclusion. The numbers of markers required to obtain 99% exclusion probabilities based on a single conflict for the three minimum MAFs were 54, 45 and 39 for scenario 1; 17, 16 and 15 for scenario 2; and 28, 25 and 24 for scenario 3. The requirement of at least two conflicts for exclusion increased the number of markers required by approximately 45% for all three scenarios and all three minimum MAFs. The results obtained by the analytical formulae were very close to results obtained by simulation and to values in the literature for specific marker sets.