A total of 6040 Israeli Holstein cows from 181 Kibbutz herds listed as progeny of 11 sires were genotyped for 104 microsatellites. Seventeen markers were deleted due to a frequency of erroneous genotypes >1%, leaving 160,470 valid genotypes. Conflicts between the putative sire and daughter in at least 2 markers and for at least 10% of the markers genotyped per cow were required to reject paternity. Cows that did not meet the requirements for paternity confirmation or rejection were deleted from further analysis. The frequency of rejected paternity was 11.7%. The effects of recorded sire, birth year, geographical region, herd, and inseminator on the frequency of paternity rejection were analyzed with linear and nonlinear models. Only the effects of inseminator and recorded sire were significant in all models tested that included these effects. The main causes of incorrect paternity recording appear to be inseminator recording mistakes, and possibly mistakes with respect to semen labeling at the AI institutes. Incorrect paternity recording due to multiple inseminations by different sires could explain, at most, 20% of the paternity mistakes. Instituting a system of quality control, especially at the level of the inseminator, should reduce paternity errors to no more than 8%, and increase genetic progress by at least 1%.

Eleven Israeli Holstein families including 5221 cows were analyzed by a daughter design for eight economic traits: milk, fat and protein production, fat and protein percentage, somatic cell score (SCS), herd-life, and female fertility. The cows were genotyped for 73 microsatellites with maximum spacing between markers of 53 cM. There were 86,304 informative genotypes. Preliminary analysis was by ANOVA of each trait, with the marker effect nested within sire. Significance was determined by controlling the false discovery rate at 0.4, after excluding markers with genome-wide significance for at least a single trait, and traits without any significant effects at this level. Thus, four markers on chromosomes 6 and 14 and female fertility were excluded. There remained 40 significant marker-trait combinations, and it is expected that 24 of these are true effects. To perform interval mapping for the families with significant contrasts, 21 additional markers were genotyped on chromosomes 2, 7, and 27. The bootstrap confidence intervals for gene effect did not include zero for protein percent on chromosome 2 and fat yield, protein yield, and SCS on chromosome 7. Quantitative trait locus heterozygosity was 33%, which is consistent with the hypothesis that only two alleles are segregating with unequal allele frequency.

Twelve bull calves were produced by mating elite Israeli cows to "Glenhapton Enhancer", a Canadian Holstein bull. The frequency of umbilical hernia (UH) in the progeny of the sons ranged from 1 to 21%, consistent with the hypothesis that Enhancer is the carrier of major dominant or codominant gene with partial penetrance for UH. Five sons of Enhancer produced progeny with >10% frequency of UH including sire 3259, whereas progeny of three sons had <3% UH. A total of 116 grand-progeny of Enhancer, all progeny of 3259, were genotyped for 59 microsatellites spanning the 29 bovine autosomes. Of these offspring, 41 were affected. Significant differences in paternal allele frequencies between the affected and unaffected progeny groups were found for marker BMS1591 on bovine chromosome 8 (BTA8). The UH-associated paternal allele originated from Enhancer. The chromosomal segment associated with UH was more precisely mapped between UWCA47, on the centromeric end of BTA8 and RM321, 12 cM from the centromere. A maximum LOD score of 3.84 was obtained 2.5 cM from the centromere with a support interval of 8 cM. Haplotype analysis of eight sons of Enhancer suggested that the UH gene is located in the centromeric end of BTA8 beyond ARO71/ARO72. Thus, by integrating the results from progeny of sire 3259 and sons of Enhancer the location of the UH gene was further refined to the BTA8 segment between ARO71/ARO72 and UWCA47.

Nine Israeli Holstein sire families with 2978 daughters were analyzed for quantitative trait loci effects on chromosome 6 for five milk production traits by a daughter design. All animals were genotyped for 2 markers. The three families with significant effects were genotyped for up to 10 additional markers spanning positions 0-122 cM of BTA6. Two sires were segregating for a locus affecting protein and fat percentage near position 55 cM with an estimated substitution effect of 0.18% protein, which is equivalent to one phenotypic standard deviation. This locus was localized to a confidence interval of 4 cM. One of these sires was also heterozygous for a locus affecting milk, fat, and protein production near the centromere. The hypothesis of two segregating loci was verified by multiple regression analysis. A third sire was heterozygous for a locus affecting milk and protein percentage near the telomeric end of the chromosome. Possible candidates for the major quantitative gene near position 55 cM were determined by comparative mapping. IBSP and SSP1 were used as anchors for the orthologous region on human chromosome 4. Twelve genes were detected within a 2-Mbp sequence. None of these genes have been previously associated with lactogenesis.

Animal GeneticsVolume 32, Issue 1 p. 40-41 A microsatellite locus has more than one copy in the genome of two tilapia species (Oreochromis aureus and O. niloticus) Y Palti, Y Palti Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorA Shirak, A Shirak Laboratory of Fish Immunology and Genetics, Department of Life Sciences, Bar Ilan University, Ramat Gan 52900, IsraelSearch for more papers by this authorA Cnaani, A Cnaani Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorE Feldmesser, E Feldmesser Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorR R Avtalion, R R Avtalion Laboratory of Fish Immunology and Genetics, Department of Life Sciences, Bar Ilan University, Ramat Gan 52900, IsraelSearch for more papers by this authorG Hulata, G Hulata Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorM Ron, M Ron Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this author Y Palti, Y Palti Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorA Shirak, A Shirak Laboratory of Fish Immunology and Genetics, Department of Life Sciences, Bar Ilan University, Ramat Gan 52900, IsraelSearch for more papers by this authorA Cnaani, A Cnaani Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorE Feldmesser, E Feldmesser Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorR R Avtalion, R R Avtalion Laboratory of Fish Immunology and Genetics, Department of Life Sciences, Bar Ilan University, Ramat Gan 52900, IsraelSearch for more papers by this authorG Hulata, G Hulata Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this authorM Ron, M Ron Institute of Animal Science, Agricultural Research Organization, P.O. Box 6, Bet Dagan 50250, IsraelSearch for more papers by this author First published: 28 June 2008 https://doi.org/10.1046/j.1365-2052.2001.0647a.xCitations: 4 M. Ron, (tel.: +972 8 9484428; fax: +972 8 9470587; e-mail: micha@agri.huji.ac.il) Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat No abstract is available for this article.Citing Literature Volume32, Issue1February 2001Pages 40-41 RelatedInformation

A genome scan was conducted in the North American Holstein-Friesian population for quantitative trait loci (QTL) affecting production and health traits using the granddaughter design. Resource families consisted of 1,068 sons of eight elite sires. Genome coverage was estimated to be 2,551 cM (85%) for 174 genotyped markers. Each marker was tested for effects on milk yield, fat yield, protein yield, fat percentage, protein percentage, somatic cell score, and productive herd life using analysis of variance. Joint analysis of all families identified marker effects on 11 chromosomes that exceeded the genomewide, suggestive, or nominal significance threshold for QTL effects. Large marker effects on fat percentage were found on chromosomes 3 and 14, and multimarker regression analysis was used to refine the position of these QTL. Half-sibling families from Israeli Holstein dairy herds were used in a daughter design to confirm the presence of the QTL for fat percentage on chromosome 14. The QTL identified in this study may be useful for marker-assisted selection and for selection of a refined set of candidate genes affecting these traits.

Twenty-one in vitro-fertilized bovine blastocysts were quartered, lysed and subjected to primer elongation preamplification (PEP) procedure, allowing for the analysis of up to 40 genotypes per quarter embryo. The quarter-embryos were sexed by polymerase chain reaction (PCR) using BRY.1, Bov97M and ZFX/ZFY loci, and then genotyped for k-casein, bovine leukocyte adhesion deficiency (BLAD) and microsatellite D9S1. The mitochondrial cytochrome B locus was used as an internal control with a 95% success rate. The PEP procedure amplified genomic fragments in 93% of all cases. The embryos were identified to be 11 males and 10 females. Sexing accuracy was 87% for BRY.1, 97% for ZFX/ZFY and 100% for Bov97M. False genotyping was due mostly to amplification of BRY.1 in the female embryos and to the nonamplification of the ZFY locus in the male embryos. The results indicate that the combined use of Bov97M and ZFX/ZFY loci is a highly accurate procedure for sexing bovine embryos. Genotyping for kappa-casein, D9S1 and BLAD was successful in 94, 99 and 91% of assays, respectively. Sex ratios and allele frequencies of embryos for gk-casein, BLAD and D9S1 were all close to the observed frequencies in the Israeli Holstein population. These results support the conclusion that the genotyping of embryos is as accurate as that of mature animals. Thus, marker-assisted selection can be efficiently applied at the preimplantation embryo level for loci of economic importance.

Individual loci affecting economic traits can be located using genetic linkage. Application of either daughter or granddaughter design requires determination of allele origin in the progeny. If only the sires and their progeny are genotyped, the paternal allele origin of progeny having the same genotype as the sire cannot be determined. The expected frequency of informative sons can be predicted for each sire and genetic marker from the allele frequencies in the population. The accuracy of a predictor of the frequency of informative progeny was tested on 103 grandsire x microsatellite combinations. Number of sons per grandsire varied from 24 to 129. Allele frequencies in the population were estimated by genotyping seven sires. The regression of the frequency of informative sons on the predicted frequency was 1.04 with a zero intercept model. Thus, considering the large number of genetic markers available for analysis, predicted informative frequency is a useful criterion for selection of genetic markers.