Reproducing kernel Hilbert spaces regression procedures for prediction of total genetic value for quantitative traits, which make use of phenotypic and genomic data simultaneously, are discussed from a theoretical perspective. It is argued that a nonparametric treatment may be needed for capturing the multiple and complex interactions potentially arising in whole-genome models, i.e., those based on thousands of single-nucleotide polymorphism (SNP) markers. After a review of reproducing kernel Hilbert spaces regression, it is shown that the statistical specification admits a standard mixed-effects linear model representation, with smoothing parameters treated as variance components. Models for capturing different forms of interaction, e.g., chromosome-specific, are presented. Implementations can be carried out using software for likelihood-based or Bayesian inference.
Genomic evaluations for 161,341 Holsteins were computed by using 311,725 of 777,962 markers on the Illumina BovineHD Genotyping BeadChip (HD). Initial edits with 1,741 HD genotypes from 5 breeds revealed that 636,967 markers were usable but that half were redundant. Holstein genotypes were from 1,510 animals with HD markers, 82,358 animals with 45,187 (50K) markers, 1,797 animals with 8,031 (8K) markers, 20,177 animals with 6,836 (6K) markers, 52,270 animals with 2,683 (3K) markers, and 3,229 nongenotyped dams (0K) with >90% of haplotypes imputable because they had 4 or more genotyped progeny. The Holstein HD genotypes were from 1,142 US, Canadian, British, and Italian sires, 196 other sires, 138 cows in a US Department of Agriculture research herd (Beltsville, MD), and 34 other females. Percentages of correctly imputed genotypes were tested by applying the programs findhap and FImpute to a simulated chromosome for an earlier population that had only 1,112 animals with HD genotypes and none with 8K genotypes. For each chip, 1% of the genotypes were missing and 0.02% were incorrect initially. After imputation of missing markers with findhap, percentages of genotypes correct were 99.9% from HD, 99.0% from 50K, 94.6% from 6K, 90.5% from 3K, and 93.5% from 0K. With FImpute, 99.96% were correct from HD, 99.3% from 50K, 94.7% from 6K, 91.1% from 3K, and 95.1% from 0K genotypes. Accuracy for the 3K and 6K genotypes further improved by approximately 2 percentage points if imputed first to 50K and then to HD instead of imputing all genotypes directly to HD. Evaluations were tested by using imputed actual genotypes and August 2008 phenotypes to predict deregressed evaluations of US bulls proven after August 2008. For 28 traits tested, the estimated genomic reliability averaged 61.1% when using 311,725 markers vs. 60.7% when using 45,187 markers vs. 29.6% from the traditional parent average. Squared correlations with future data were slightly greater for 16 traits and slightly less for 12 with HD than with 50K evaluations. The observed 0.4 percentage point average increase in reliability was less favorable than the 0.9 expected from simulation but was similar to actual gains from other HD studies. The largest HD and 50K marker effects were often located at very similar positions. The single-breed evaluation tested here and previous single-breed or multibreed evaluations have not produced large gains. Increasing the number of HD genotypes used for imputation above 1,074 did not improve the reliability of Holstein genomic evaluations.
A feed efficiency experiment was conducted in a population consisting of progeny from 10 full sib families of a cross between two broiler lines. Microsatellite genotypes were determined on Generation (G) 1 and 2. In G3, BW at 23 and 48 d and feed intake were measured and were used to calculate growth between 23 and 48 d, feed intake adjusted for BW, and feed efficiency. Average adjusted progeny trait values were calculated for G2 animals after adjusting phenotypic observations on offspring for fixed effects, covariables, maternal genetic effects, the additive genetic contribution of the mate, and heterogeneity between sexes and were used as dependent variable in the quantitative trait loci (QTL) analysis. A full sib interval mapping approach was applied using genotypes from 420 markers on 27 autosomal linkage groups. Four QTL exceeded significance thresholds. The most significant QTL was located on Chromosome 1 at 235 cM and had a 4% genomewise significance for feed intake between 23 and 48 d. Furthermore, this QTL exceeded suggestive linkage for growth between 23 and 48 d and BW at 48 d. A second QTL was located on linkage group WAU26 at 16 cM and showed suggestive linkage for feed intake between 23 and 48 d. On Chromosome 4, at 147 cM a third QTL, which had an effect on both feed intake traits, was found. Finally, a fourth QTL, which affected feed intake adjusted for BW, was located on Chromosome 2 at 41 cM.
RIASSUNTO -Effetto delloKEY WORDS: heat tolerance, temperature-humidity index (THI), dairy sheep.INTRODUCTION -European Mediterranean countries are characterized by exposure to considerable heat between three and six months annually. High ambient temperature, solar radiation, wind speed and relative humidity, cause the effective temperature of the environment to be above the thermo-neutral zone of the animals (5 to 25ºC; McDowell, 1972) and therefore heat stress occurs (Bianca, 1962). Heat stress is one of the limiting factors in dairy production in hot climates (Johnson et al., 1962) and is hard to account for by management in the extensive grazing-based farming system of Mediterranean dairy sheep where animals are rarely kept indoors. The interest of our study was to investigate if in the Mediterranean area heat stress has an effect on dairy sheep performance. Some studies (Ames et al., 1971;Sevi et al., 2001) on sheep heat stress investigated changes in rectal temperatures, respiration rates, volumes of air inhaled and other physiological functions. Unfortunately, such measurements are costly and not feasible on a large scale in practical farming circumstances, which leads to insufficient data quantity, especially for genetic studies. In the present paper the methodology of Ravagnolo et al. (2000) based on using weather station data for Holstein cattle was applied to Valle del Belice dairy sheep. The animals were investigated with the following aims: to establish the relationship between production and weather conditions using information from a weather station, and to estimate the additive genetic variances of milk production traits and heat tolerance, and therefore to investigate the possibility of future selection for increased heat tolerance.
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