Academic literature on the topic 'Progeny test value'
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Journal articles on the topic "Progeny test value"
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Marnis, Huria, Bambang Iswanto, Romy Suprapto, Imron Imron, and Raden Roro Sri Pudji Sinarni Dewi. "IDENTIFIKASI ZIGOSITAS IKAN LELE (Clarias gariepinus) TRANSGENIK F-2 YANG MEMBAWA GEN HORMON (PhGH) DENGAN MENGGUNAKAN METODE REALTIME-qPCR." Jurnal Riset Akuakultur 11, no. 1 (November 14, 2016): 39. http://dx.doi.org/10.15578/jra.11.1.2016.39-46.
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Produktivitas ikan budidaya dapat ditingkatkan melalui teknologi transgenesis. Populasi ikan lele transgenik cepat tumbuh telah dihasilkan dan karakter biologisnya telah diketahui. Namun informasi zigositas ikan lele transgenik perlu ditelaah lebih lanjut. Penelitian ini bertujuan untuk mengidentifikasi zigositas ikan lele transgenik F-2. Zigositas ikan lele transgenik diidentifikasi dengan menggunakan metode real-time qPCR (RT-qPCR) dan uji progeni. Identifikasi zigositas melalui uji progeni, dilakukan dengan mendeteksi transgen (PhGH) pada individu-individu F-3 hasil persilangan transgenik F-2 dengan non-transgenik. Hasil penelitian menunjukkan bahwa zigositas pada ikan lele transgenik F-2 dapat diidentifikasi dengan menggunakan metode RT-qPCR. Semua ikan transgenik F-2 adalah heterozigot, dengan nilai 2-Ct yang hampir sama tiap individu F-2, yaitu berkisar 0,80-0,99. Identifikasi zigositas dengan metode RT-qPCR menunjukkan hasil yang sama dengan uji progeni, semua transgenik F-2 tidak menghasilkan 100% anakan F-3 positif transgen. Pada uji progeni, transmisi transgen pada penelitian ini tidak mengikuti hukum segregasi Mendel, dengan kisaran sebesar 5%-40%.Fish farming productivity can be increased by transgenesis technology. On the previous study, transgenic African catfish population fast growing has been produced and its biological characters has been known. However information of transgenic zygosity of catfish should be examined. The aim of this study was to identify the zygosity of F-2 transgenic African catfish. The zygosity of F-2 transgenic was identified by real time-qPCR (RT-qPCR) method and progeny test. Further, identification of zygosity F-2 transgenic African catfish was confirmed by progeny test, while F-2 transgenic African catfish was mated with non-transgenic. Identification of zygosity F-2 transgenic was conducted by detection PhGH gene (transgene) in F-3 transgenic African catfish population. Transgene transmission was evaluated by PCR method. The result showed that the zygosity F-2 transgenic African catfish could be identified by RT-qPCR method. All F-2 transgenic African catfish were heterozygous, where as the 2-Ct value was almost same for all individual, which ranges from 0.80 to 0.99. The result of zygosity identification using RT-qPCR method was as same as that of progeny test. In the progeny test, transgene transmission in this study was non-Mendelian segregation, with ranges of 5%-40%.
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Woolliams, J. A., and C. Smith. "The value of indicator traits in the genetic improvement of dairy cattle." Animal Production 46, no. 3 (June 1988): 333–45. http://dx.doi.org/10.1017/s0003356100018948.
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ABSTRACTThe value of indicator traits (7), such as physiological or biochemical traits in the genetic improvement of dairy cattle for milk yield (M) was studied. First, some corrections were made to the base rates of genetic change possible by improvement systems based on progeny testing and on multiple ovulation and embryo transfer (MOET), and on combinations of these. Efficient field progeny-testing systems can be competitive with current adult MOET nucleus herd schemes but juvenile MOET nucleus herd schemes offer substantial increases in rates of response. With high co-heritability, selection for the T alone may allow greater rates of response than those currently considered feasible using progeny testing. However, faster rates are obtained with combined selection. When breeding values are accurately measured by pedigree and performance records on M, as in the progeny test, the extra rates of response with combined selection may be small. Where breeding values are less accurately assessed, as in juvenile MOET nucleus schemes, the extra rates of response can be appreciable. For T with co-heritability (hMrGhT) of 0·27 and the CV for M from 0·15 to 0·20, response rates of 2·0 to 2·7% of the mean per year possible by traditional methods could be increased to 2·2 to 2·9% in progeny testing schemes, 2·3 to 3·1% and to 4·3 to 5·7% for adult and juvenile MOET nucleus schemes respectively.A possible useful indicator trait is blood urea nitrogen (BUN) measured in young animals after a short fast. Results from four experiments with calves having high or low genetic merit for M were summarized. The pooled co-heritability estimate was —0·27 (s.e. 0·05). With this, or even a more modest effect, BUN would be a useful indicator trait in selection for milk production. Its use in practice in high and low selection lines or in a section of the industry, would allow assessment of the merit of the method.
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Meland, O. "Procedures of sire selection, sampling and application of new technology." BSAP Occasional Publication 19 (1995): 9–12. http://dx.doi.org/10.1017/s0263967x00031748.
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AbstractThe objective of any well designed progeny test programme is to identify those individuals that have inherited the favourable genes from his parents. Bulls that enter a progeny test programme have been highly selected on a set of selection criteria. The criteria vary among organizations based upon their breeding philosophy and their prediction of the future economic value of various traits. The accuracy of choosing among this highly selected group is quite low. Increasing the accuracy of selection before progeny testing is the greatest potential application of genetic marker technology. Markers associated with traits of importance can greatly enhance traditional selection methods by increasing the prospect of an individual having the desired characteristics. Genetic marker-assisted selection can greatly increase the actual genetic merit of traits of economic importance
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Hill, William G., and Karin Meyer. "Developments in methods for breeding value and parameter estimation in livestock." BSAP Occasional Publication 12 (1988): 81–98. http://dx.doi.org/10.1017/s0263967x0000330x.
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In an effective animal breeding programme the objectives are appropriate, the population structure is good, suitable records are collected, and these records are used in an optimal way so that animals likely to have the best offspring are chosen.Estimates of genetic parameters such as heritabilities and correlations influence the design of the programme: for example, the optimal number of daughters to progeny test per dairy sire or, more fundamentally, whether to adopt performance or progeny testing, whether to record food conversion efficiency or simply growth rate, and whether or not to collect records on some indicator trait such as blood urea nitrogen level. The estimates of parameters also influence the weightings given to different traits and to individuals and relatives' performance in breeding value estimation and selection. Methods for estimating parameters have become much more sophisticated as a result of advances in theory, particularly, restricted maximum likelihood (REML), in computer power, and in development of special computer programs.
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Swanson, G. J. T., and H. Joanne Bellamy. "A comparison between the actual progeny test of Friesian/Holstein bulls and indexes calculated from pedigree information." Animal Production 48, no. 1 (February 1989): 37–41. http://dx.doi.org/10.1017/s0003356100003767.
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ABSTRACTTwo pedigree indexes were calculated for 754 Friesian/Holstein bulls born between 1974 and 1980 and tested by the Milk Marketing Board. Correlations between the indexes and the average progeny performance were used to compare the indexes calculated using information from different ancestors. The first index, or estimated predicted difference (EPD) was calculated as one-half the sire progeny test, known as an Improved Contemporary Comparison (ICC), plus one-quarter the maternal grandsire ICC. The second index or estimated ICC (EICC) was calculated from one-half the sire ICC plus one-half the dam cow genetic index (CGI). The correlations between the deregressed bull evaluations (DICC) and EPD, calculated from 310 bulls, were 0·40 for milk yield, 0·40 for fat yield and 0·39 for protein yield. The corresponding correlations between the DICC and EICC, calculated from 314 bulls, were 0·43, 0·40 and 0·41. The regression coefficients for predicting average progeny performance from the EPD index were 1·00 (s.e. 0·13), 0·97 (s.e. 0·12), 0·96 (s.e. 0·13), 1·09 (s.e. 0·12) and 1·08 (s.e. 0·10) for milk, fat and protein yield, fat and protein percentage respectively. Those for predicting progeny performance from the EICC index were 0·95 (s.e. 0·11), 0·81 (s.e. 0·10) and 0·84 (s.e. 0·10) for milk, fat and protein yield respectively. Although the correlations were lower than the expected values of 0·50 (EPD) and 0·55 (EICC) the regressions were near the expected value of 1. The results indicate that the indexes are useful as a preliminary means of selecting bulls prior to progeny testing.
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Mardenli, Omar R. "The Progeny test of Friesian sires for milk traits by using the contemporary comparison method." Revista Colombiana de Ciencia Animal - RECIA 13, no. 1 (March 11, 2021): e747. http://dx.doi.org/10.24188/recia.v13.n1.2021.747.
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In this study, the contemporary comparison method (CC) of half-sibs relation was used to estimate the breeding values of Holstein-Friesian sires for 305 -day milk yield (305-DMY) and basic components of milk traits, 409 records of cows that are daughters of ten sires in eight Syrian dairy farms where used. Result of the study showed differences in the estimated breeding values(ccEBVs), where the E Sire achieved the highest value of 305-DMY trait (254.47 kg), while the B Sire achieved the highest value of milk protein percentage (MPP), milk fat percentage (MFP)and milk lactose percentage (MLP) traits (0.822 %, 0.857 %and 1.09% respectively). According to their sires, daughters of E Sire outperformed the counterparts in the 305-DMY (p = 0.001), MPP (p = 0.001) and MFP (p = 0.04) traits (5701.44 kg, 3.55%, and 3.88% respectively). According to source of farm, daughters in Farm 5 achieved the highest value of 305-DMY trait (p=0.04) and daughters in the seventh farm achieved the highest value of MPP trait (p=0.007), the values were 5403.48 kg and 3.54 % respectively. Values of heritability (h2) for the traits of 305-DMY, MPP, MFP and MLP were 0.33,0.54,0.43 and 0.47 respectively. Most of genetic and phenotypic correlations coefficients were approaching to zero except the genetic relation between MLP and MPP and phenotypic relation between MFP and MPP (0.88 and 0.84 respectively).
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Apiolaza, Luis A., Arthur R. Gilmour, and Dorian J. Garrick. "Variance modelling of longitudinal height data from a Pinus radiata progeny test." Canadian Journal of Forest Research 30, no. 4 (April 1, 2000): 645–54. http://dx.doi.org/10.1139/x99-246.
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Variance components were estimated using alternative structures for the additive genetic covariance matrix (G0), for height (m) of trees measured at 10 unequally spaced ages in an open-pollinated progeny test. These structures reflected unstructured, autoregressive, banded correlation and random regressions models. The residual matrix (R0) was unstructured, and the block and plot strata matrices were autoregressive. The best model for G0 considering the likelihood value and number of parameters was the autoregressive correlation form with age-specific variances and time on a natural logarithm basis. The genetic correlation between successive measures ranged from 0.93 at age 1 to 0.99 at age 14 years. Heritability increased with age from 0.09 (age 1) to 0.24 (age 7) and then declined to 0.13 at age 15. Heritabilities from the unstructured model were similar, while heritabilities assuming banded correlations were lower after age 7. The covariance structure implicit in the random regressions model was considered unsatisfactory. Using structures in G0 facilitated model fitting and convergence of the likelihood maximisation algorithm. Fitting a structured matrix that reflects the relationships present in repeated measures may overcome problems of nonpositive definiteness of unstructured matrices from longitudinal data, especially when genetic variation is small.
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Weaver, Andrew R., Donald L. Wright, and Scott P. Greiner. "125 Utilization of Performance-tested and NSIP Sires Improved Progeny Performance and Value in Ram Test Program." Journal of Animal Science 100, Supplement_1 (March 8, 2022): 44. http://dx.doi.org/10.1093/jas/skac028.082.
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Abstract Sire selection can have long-term impacts on flock performance. The objective here was to evaluate the effect of performance-tested and/or NSIP rams on progeny performance and value in a ram test program. Rams (Katahdin = 104, Dorper = 7, Texel = 3, Cheviot = 3) were delivered to the Southwest Virginia Agricultural Research and Extension Center (SWAREC) Ram Test on June 1. Ram pedigrees were obtained from consignors and rams were classified based on whether their sires were tested in a previous SWAREC Ram Test (TESTED), enrolled in the National Sheep Improvement Program (NSIP), or neither TESTED nor NSIP (NEITHER). Some sires (16%) were previously tested and enrolled in NSIP. Rams were dewormed and rested for two weeks. On June 22, rams were given Haemonchus contortus larvae adjusted for body weight (average = 5000 L3). FAMACHA scores and fecal egg counts (FEC) were monitored every two weeks until August 31. Rams were dewormed based on FAMACHA ≥ 3. Select rams were sold at auction as breeding stock. Statistical analysis were performed using SAS (SAS Institute, Cary, NC). Rams requiring deworming had greater FAMACHA scores and FEC at all time points (P < 0.05), despite not requiring treatment until August 17 (5%) and August 31 (12%). In total, 17% of rams were dewormed. Of the dewormed rams, a smaller portion of rams sired by TESTED rams (10%) and NSIP rams (15%) required treatment compared to rams sired by NEITHER rams (85%; P < 0.05). Rams sired by TESTED and NSIP rams had a higher average value than those sired by NEITHER rams ($2070 and $1838, respectively, vs. $1078; P < 0.05). Selection of sires that are TESTED and/or NSIP resulted in progeny that had a lesser chance of requiring treatment and sold for greater value.
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Meuwissen, T. H. E. "A deterministic model for the optimization of dairy cattle breeding based on BLUP breeding value estimates." Animal Science 49, no. 2 (October 1989): 193–202. http://dx.doi.org/10.1017/s0003356100032311.
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ABSTRACTA deterministic model was developed to examine the optimization of open nucleus breeding schemes in order to maximize the rate of genetic response in dairy cattle. By changing the parameters, the model was able to simulate both a closed nucleus and a progeny testing scheme. The model implicitly optimized the generation interval and the selection across tiers by means of truncation across age classes and tiers respectively. The effects of size of the progeny test group and the nucleus size were assessed by comparing alternative plans. It is possible to optimize a breeding plan given the reproduction rates of the animals, the availability of different sources of information, the age distribution of the animals (survival rates) and the phenotypic and genetic parameters of the trait.The steady state selection response was assessed by calculating the genetic progress year after year until it stabilized. The genetic gain was corrected for the effects of reduced variances due to previous selections and increased variances due to genetic differences between parental age classes.In an example, the model was used to predict the improvement in milk yield in a closed artificial insemination breeding scheme. The genetic gain of a conventional progeny testing scheme was about one-third lower than the genetic gain of the optimized breeding plan. The variance reduction due to selection decreased the steady state genetic gain by a factor 0·3
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Gonçalves, Paulo de Souza, Mário Luiz Teixeira de Moraes, Marcelo de Almeida Silva, Lígia Regina Lima Gouvêa, Adriano Tosoni da Eira Aguiar, and Reginaldo Brito da Costa. "Prediction of Hevea progeny performance in the presence of genotype-environment interaction." Brazilian Archives of Biology and Technology 52, no. 1 (February 2009): 25–33. http://dx.doi.org/10.1590/s1516-89132009000100004.
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Twenty two open-pollinated Hevea progenies from different parental clones of the Asian origin were tested at five sites in the Northwestern São Paulo State Brazil to investigate the progeny girth growth, rubber yield, bark thickness and plant height. Except for the rubber yield, the analysis of variance indicated highly significant (p<0.01) genotype x environment interaction and heterogeneity of regressions among the progenies. However, the regression stability analysis identified only a few interacting progenies which had regression coefficients significantly different from the expected value of one. The linear regressions of the progeny mean performance at each test on an environmental index (mean of all the progenies in each test) showed the general stability and adaptability of most selected Hevea progenies over the test environments. The few progenies which were responsive and high yielding on different test sites could be used to maximize the rubber cultivars productivity and to obtain the best use of the genetically improved stock under different environmental conditions.
Dissertations / Theses on the topic "Progeny test value"
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Su, Susi Li-Ho, and 蘇力禾. "Estimating Breeding Values and Genetic Gain of Cunninghamia lanceolata (Lamb.) Hook. var. konishii from a 27-Year Progeny Test with Messy Data." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/12115943281512963508.
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碩士國立中興大學
森林學系
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Eighteen open-pollinated (OP) families of a local variety of China fir (Cunninghamia lanceolata (Lamb.) Hook. var. konishii) were grown in a field trial to evaluate the magnitude of genetic parameter estimates and ranking of the parental clones, for growth (height, DBH, and diameter at basal area; DBA) and wood density traits up to 27 years. The field-trial layout was randomized complete block design (RCBD) with four adjacent south-north longitudinal blocks. After checking the intra-class correlations it was found that it would be better to divide the 4 east-west blocks into 2 south-north blocks, so that the long axis of the block is parallel to the contour. That made the field design incomplete blocks. It was also found that edge effects seriously influenced the stem diameter growth for the border trees. We therefore also deleted those seriously biased border trees from the data. Statistical analyses showed second-year height and 27-year wood density were not influenced by environmental impacts, and there were no significant differences among families. Other growth traits (six-year height, 25-year height, 25-year DBH, 25-year DBA, 25-year stem volume, relative growth between second- and six-year heights, and relative growth between six- and 25-year heights) showed significant differences among families and among blocks. Height growth (second-year and 25-year heights) showed significant family by block interactions. Stem diameter growth (25-year DBH, DBA, and Volume) traits had no interactions at all. Tree height between ages demonstrated substantial genetic correlation (0.61). Tree height and stem diameters of the same age also exhibited substantial genetic correlations (0.59). Twenty-seven-year wood density showed no family variation. Twenty-five-year height showed high individual-tree heritability. Heritability estimates increased as the trees grew older. Height growth traits in general have higher heritabilities than stem diameter growth. Using one unit of standard phenotypic deviation as selection differential to estimate genetic gain would result in 2.29m in 25-year height, 2.34cm in 25-year DBH, and 0.08m3 in 25-year stem volume. Using six-year height as an early-selection trait, indirect selection would result in 1.10m gain in 25-year height. This is equivalent to 0.18m per year, which is much higher than a gain of 0.09m direct selection in 25-year height. No matter whether family effect is taken as “fixed effect” or “random effect”, arithmetical means and BLUP values showed high correlations (0.9231~0.9572), which implies that both are reliable estimates of the breeding values. Using BLUP values to rank families, five families were both selected into the top nine families for tree height at different ages. Using bi-character (25-year height and DBH) to adjust the estimate of breeding values of 25-year DBH is effective. The improvement magnitude of the top nine families is from 10.29% to 0.97%. This method was therefore proven to be a superior strategy of multi-trait selection. Current research results provide a useful reference for genetic selection of China fir in the future.
Books on the topic "Progeny test value"
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Robinson, Majied. Statistical Approaches to the Rise of Concubinage in Islam. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190622183.003.0002.
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A statistical analysis of an early Arabic text, Nasab Quraysh of al-Zubayri (d.c. 850), is used to examine the rise of concubinage during the first period of Islamic history. Using basic prosopographical and statistical techniques, the author argues for a sharp rise in reliance on concubinage by elite Arab families following the appearance of Islam during the seventh century CE. Contrary to what is often claimed, concubines and their progeny enjoyed a significant presence in elite Arab families well before the Abbasid era, and there is little evidence to suggest that either mothers or their offspring were discriminated against on a systematic basis. The value of new methods of reading medieval Arabic texts is emphasized in an effort to reconstruct the history of gender and slavery in Islamic history.
Book chapters on the topic "Progeny test value"
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White, Timothy L., and Gary R. Hodge. "Concepts of Progeny Test Analysis." In Predicting Breeding Values with Applications in Forest Tree Improvement, 48–61. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-7833-2_3.
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White, Timothy L., and Gary R. Hodge. "Best Linear Prediction with Half-sib Progeny Test Data." In Predicting Breeding Values with Applications in Forest Tree Improvement, 86–110. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-015-7833-2_5.
Full textReports on the topic "Progeny test value"
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Weller, Joel I., Ignacy Misztal, and Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, March 2015. http://dx.doi.org/10.32747/2015.7594404.bard.
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The main objectives of this research was to detect the specific polymorphisms responsible for observed quantitative trait loci and develop optimal strategies for genomic evaluations and selection for moderate (Israel) and large (US) dairy cattle populations. A joint evaluation using all phenotypic, pedigree, and genomic data is the optimal strategy. The specific objectives were: 1) to apply strategies for determination of the causative polymorphisms based on the “a posteriori granddaughter design” (APGD), 2) to develop methods to derive unbiased estimates of gene effects derived from SNP chips analyses, 3) to derive optimal single-stage methods to estimate breeding values of animals based on marker, phenotypic and pedigree data, 4) to extend these methods to multi-trait genetic evaluations and 5) to evaluate the results of long-term genomic selection, as compared to traditional selection. Nearly all of these objectives were met. The major achievements were: The APGD and the modified granddaughter designs were applied to the US Holstein population, and regions harboring segregating quantitative trait loci (QTL) were identified for all economic traits of interest. The APGD was able to find segregating QTL for all the economic traits analyzed, and confidence intervals for QTL location ranged from ~5 to 35 million base pairs. Genomic estimated breeding values (GEBV) for milk production traits in the Israeli Holstein population were computed by the single-step method and compared to results for the two-step method. The single-step method was extended to derive GEBV for multi-parity evaluation. Long-term analysis of genomic selection demonstrated that inclusion of pedigree data from previous generations may result in less accurate GEBV. Major conclusions are: Predictions using single-step genomic best linear unbiased prediction (GBLUP) were the least biased, and that method appears to be the best tool for genomic evaluation of a small population, as it automatically accounts for parental index and allows for inclusion of female genomic information without additional steps. None of the methods applied to the Israeli Holstein population were able to derive GEBV for young bulls that were significantly better than parent averages. Thus we confirm previous studies that the main limiting factor for the accuracy of GEBV is the number of bulls with genotypes and progeny tests. Although 36 of the grandsires included in the APGD were genotyped for the BovineHDBeadChip, which includes 777,000 SNPs, we were not able to determine the causative polymorphism for any of the detected QTL. The number of valid unique markers on the BovineHDBeadChip is not sufficient for a reasonable probability to find the causative polymorphisms. Complete resequencing of the genome of approximately 50 bulls will be required, but this could not be accomplished within the framework of the current project due to funding constraints. Inclusion of pedigree data from older generations in the derivation of GEBV may result is less accurate evaluations.