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PubMed2001

Estimation of the genetic parameters of meat characteristics and of their genetic correlations with growth and body composition in an experimental broiler line.

Genetic parameters of breast meat characteristics [pH 15 min postmortem (pH15min), ultimate pH (pHu), CIELAB color parameters (L*, lightness; a*, redness; b*, yellowness) and drip loss (DL)] as well as their genetic correlations with BW and body composition [breast yield (BRY) and abdominal fat percentage (AFP)] were estimated in an experimental meat-type chicken line. Heritability of the pH of meat was high for pHu (0.35 +/- 0.03) and even more so for pH15min (0.49 +/- 0.01). Color parameters appeared to be the most heritable traits, with heritability values ranging from 0.50 to 0.57. Drip loss heritability was estimated at 0.39 +/- 0.04. The rate and the extent of pH decline seemed to be controlled by different genes, as shown by the extremely low estimated genetic correlation (0.02 +/- 0.04) between pH15min and pHu. The ultimate pH of the meat was genetically very strongly related to its lightness (-0.91 +/- 0.02) and water-holding capacity (-0.83 +/- 0.04). These results suggest that selection for pHu could be exploited to prevent increased incidence of pale and exudative meat. The pH15min was poorly correlated with the other meat characteristics, with estimated correlations of 0.13, -0.23, 0.05, and -0.29 for L*, a*, b*, and DL, respectively. These results may be explained by the fact that, in our experimental conditions, pH15min remained high (between 6.01 and 6.75). Body weight and BRY exhibited poor genetic correlations (ranging from -0.06 to 0.13) with the pH of the meat at 15 min and 24 h postmortem. Both of the former traits were moderately negatively correlated with a* and b* values. A significant negative genetic correlation was observed between abdominal fatness and pHu. These results do not support the idea that selection for growth and breast development has a detrimental effect on breast meat quality even if, in the long term, the color intensity could be decreased.

Animals↗

PubMed2007

Environmental influence on the genetic correlations between life-history traits in Caenorhabditis elegans.

Empirical evidence is mounting to suggesting that genetic correlations between life-history traits are environment specific. However, detailed knowledge about the loci underlying genetic correlations in different environments is scant. Here, we studied the influence of temperature (12 degrees C and 24 degrees C) on the genetic correlations between egg size, egg number and body mass in the nematode Caenorhabditis elegans. We used a quantitative trait loci (QTL) approach based on a genetic map with evenly spaced single nucleotide polymorphism markers in an N2 x CB4856 recombinant inbred panel. Significant genetic correlations between various traits were found at both temperatures. We detected pleiotropic or closely linked QTL, which supported the negative correlation between egg size and egg number at 12 degrees C, the positive correlation across temperatures for body mass, and the positive correlation between body mass and egg size at 12 degrees C. The results indicate that specific loci control the covariation in these life-history traits and the locus control is prone to environmental conditions.

Animals↗

PubMed1984

Genetic correlations of pig performance and sow productivity traits.

Records for a total of 732 daughter-dam pairs were analyzed to estimate the genetic correlations of pig performance traits with sow productivity traits, with implications to the development of specialized sire and dam lines for use in crossing. Major pig performance traits analyzed included average daily gain from 56 d of age to a final weight of 90.7 kg (ADG), average backfat thickness at 90.7 kg (BF) and a performance index (PI) consisting of ADG and BF. Major sow productivity traits included number of pigs born alive in a litter (NA), litter size (N21) and litter weight (W21) at 21 d of age and two sow productivity indexes, one with NA, N21 and W21 (SPI-3) and one with NA and W21 (SPI-2). All records were expressed as deviations from breed-line-year-season means of this population. Genetic correlations were computed from daughter-dam covariances. The mean genetic correlation of PI with SPI consisted of two correlations, that of daughters' PI with dams' SPI and that of dams' PI with daughters' SPI. The mean genetic correlation of PI with SPI-3 and SPI-2 was .07 +/- .12, suggesting that concurrent improvement in both PI and SPI would not be restricted by selection within a single composite line. The genetic correlation of daughters' PI with dams' SPI (-.18 +/- .13) was appraised as more critical than the reciprocal correlation of dams' PI with daughters' SPI (+.28 +/- .13). This appraisal is based on the fact that only one generation separates a daughter's PI from her dam's SPI, as compared with two generations in the reciprocal covariance. However, the -.18 correlation was not significantly different from zero, indicating that formation of specialized sire and dam lines for use in crossing would be only marginally more effective at best for improving the overall efficiency in pork production than use of a single composite line, aside from the heterosis effects from crossing the lines. Indexes were proposed for combining PI and SPI for use either in specialized sire and dam lines or in a single composite line.

Animals↗

PubMed1986

Heritabilities and genetic correlations of growth and reproductive measurements in Hereford bulls.

Weight, hip height, heart girth, pelvic height, pelvic width and scrotal circumference were measured at 403 and 490 d on 427 Hereford bulls. The bulls were members of a random-selection herd so estimates of genetic parameters should have a minimum of bias due to selection. Heritabilities and genetic correlations were estimated by normal paternal half-sib (PHS) correlation procedures. In addition, 256 son-sire pairs (RSS) were used to estimate heritabilities and genetic correlations by regression and covariance methods. The PHS method produced heritability estimates in the range of .41 to .58 for all measures at both ages, with the exceptions of hip height at 403 d (.24) and pelvic height at 490 d (.23). The estimates derived in the RSS method ranged from .10 to .60. The RSS relationship would contain a portion of any maternal X direct covariance effects. A difference in heritability estimated by the two methods could be a reflection of this covariance. Genetic correlations tended to be larger than phenotypic and, in several cases, were negative. The difference in the correlation between two measurements taken at 403 d vs the same correlation estimated at 490 d was not readily explainable but may be evidence for differences in maturation rates or maternal effects. Scrotal circumference had a positive genetic correlation with weight and heart girth and near 0 or negative genetic correlations with pelvic measures. Hip height had positive genetic correlations with weight and heart girth at 403 and 490 d and with pelvic measurements at 403 d, but the correlations were not as large at 490 d.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

PubMed2001

Estimating genetic correlations from measurements of field-caught waterstriders.

Lynch (1999) proposed a method for estimation of genetic correlations from phenotypic measurements of individuals for which no pedigree information is available. This method assumes that shared environmental effects do not contribute to the similarity of relatives, and it is expected to perform best when sample sizes are large, many individuals in the sample are paired with close relatives, and heritability of the traits is high. We tested the practicality of this method for field biologists by using it to estimate genetic correlations from measurements of field-caught waterstriders (Aquarius remigis). Results for sample sizes of less than 100 pairs were often unstable or undefined, and even with more than 500 pairs only half of those correlations that had been found to be significant in standard laboratory experiments were statistically significant in this study. Statistically removing the influence of environmental effects (shared between relatives) weakened the estimates, possibly by removing some of the genetic similarity between relatives. However, the method did generate statistically significant estimates for some genetic correlations. Lynch (1999) anticipated the problems found, and proposed another method that uses estimates of relatedness between members of pairs (from molecular marker data) to improve the estimates of genetic correlations, but that approach has yet to be tested in the field.

Animals↗

PubMed1991

Ovulation rate and twinning rate in cattle: heritabilities and genetic correlation.

Repeated measures of ovulation rate on puberal heifers should be an effective way to select for increased twinning rate. A reliable estimate of the genetic correlation between ovulation and twinning rates is needed to implement such selection and to predict its efficiency. Restricted maximum likelihood was used to estimate genetic correlations from subsets of data collected from the twinning project at the Roman L. Hruska U.S. Meat Animal Research Center. The animal model included numerator relationships among the animals and fixed effects of year-season of measurement, age at measurement, and birth group. Genetic correlations between averages of ovulation rates for three, four, five, six, seven, and eight estrous cycles and the occurrence of twins were, respectively, .62, .76, 1.00, 1.00, 1.00, and .98 based on observations on 200 to 325 puberal heifers. Corresponding phenotypic correlations ranged from .06 to .26. Genetic correlations between ovulation rate in a single estrous cycle and occurrence of twins were .38, .98, and .98, respectively, for 323, 430, and 283 cows with ovulation rate measured after measurement of twinning, in the same season as measurement of twinning, and more than 1 yr before measurement of twinning. Phenotypic correlations were .00, .07, and .00. Genetic and phenotypic correlations among ovulation rates at six consecutive estrous cycles averaged, respectively, .66 and .12 for 610 heifers. Heritabilities for ovulation rates in individual cycles averaged .16. No evidence of negative environmental covariance between ovulation rates in adjacent cycles was found. These results support the approach of indirectly selecting for twinning rate by measuring ovulation rates in estrous cycles of puberal heifers.

Animals↗

PubMed2006

Heritability and genetic correlation estimates for performance and carcass and body composition traits in a male broiler line.

The current research was conducted to estimate the heritability coefficients and the genetic correlations for performance and carcass and body composition traits in a single sire broiler line. The performance traits analyzed were BW at 38 d, ultrasound records of pectoral muscle depth, feed intake, feed conversion ratio, and BW at 42 d. The carcass traits analyzed were eviscerated BW, breast weight, and leg weight, and the body composition traits analyzed were abdominal fat content, heart weight, gizzard weight, liver weight, and intestine weight. The number of observations varied between 4,120 and 29,040 for each trait. The (co)variance components, heritability, and genetic correlation estimates were obtained by restricted maximum likelihood. The numerator relationship matrix had 42,912 animals. Based on the heritability estimates obtained, the analyzed traits seemed to be able to respond to selection, at variable intensities. The genetic correlation estimates between a great number of performance traits, as well as between a great number of carcass traits, were suggestive of a close genetic relationship between these traits. The genetic correlation estimates between body composition traits were variable. A large genetic association between a great number of performance and carcass traits seemed to exist. The genetic correlation estimates between performance and body composition traits were variable, and important associations between carcass and body composition traits did not seem to exist.

Abdominal Fat↗

PubMed2006

Genetic correlations between live yearling bull and steer carcass traits adjusted to different slaughter end points. 1. Carcass lean percentage.

We studied genetic relationships between age-constant live yearling beef bull growth and ultrasound traits and steer carcass traits with dissected steer carcass lean percentage adjusted to slaughter age-, HCW-, fat depth-, and marbling score-constant end points. Three measures of steer carcass lean percentage were used. Blue Tag lean percentage (BTLean) was predicted from HCW, fat depth, and LM area measurements. Ruler lean percentage (RulerLean) was predicted from carcass fat depth and LM depth and width measurements. Dissected lean percentage (DissLean) was based on dissection of the 10-11-12th rib section. Both BTLean (h2 = 0.30 to 0.44) and DissLean (h2 = 0.34 to 0.39) were more heritable than RulerLean (h2 = 0.05 to 0.14) at all end points. Genetic correlations among DissLean and RulerLean (rg = 0.61 to 0.70), DissLean and BTLean (rg = 0.56 to 0.72), and BTLean and RulerLean (rg = 0.59 to 0.90) indicated that these traits were not genetically identical. Adjusting Diss-Lean to different end points changed the magnitude, but generally not the direction, of genetic correlations with indicator traits. Ultrasound scan-age-constant live yearling bull lean percentage estimates were heritable (h2 = 0.26 to 0.42) and genetically correlated with each other (rg = 0.68 to 0.99) but had greater correlations with DissLean at slaughter age (rg = 0.24 to 0.48) and HCW (rg = 0.16 to 0.40) end points than at fat depth (rg = -0.08 to 0.13) and marbling score (rg = 0.02 to 0.11) end points. Scan-age-constant yearling bull ultrasound fat depth also had stronger correlations with DissLean at slaughter age (rg = -0.34) and HCW (rg = -0.25) than at fat depth (rg = -0.02) and marbling score (rg = -0.03) end points. Yearling bull scan-age-constant ultrasound LM area was positively correlated with DissLean at all endpoints (rg = 0.11 to 0.23). Genetic correlations between yearling bull LM method 1 width (rg = 0.38 to 0.56) and method 2 depth (rg = -0.17 to -0.38) measurements with DissLean suggested that LM shape may be a valuable addition to genetic improvement programs for carcass lean percentage at slaughter age, HCW, and fat depth constant end points. At all end points, steer carcass fat depth (rg = -0.60 to -0.64) and LM area (rg = 0.48 to 0.59) had stronger associations with DissLean than did corresponding live yearling bull measurements. Improved methods that combine live ultrasound and carcass traits would be beneficial for evaluating carcass lean percentage at fat depth or marbling score end points.

Adipose Tissue↗

PubMedDate not supplied

Phenotypic and genetic correlations among floral traits in two species of Thalictrum.

The evolution of dioecy in plants is expected to be followed by sex-specific selection, leading to sexual dimorphism. The extent of the response to selection depends on the genetic covariance structure between traits both within and between the sexes. Here I describe an investigation to determine phenotypic and genetic correlations between reproductive traits within cryptically dioecious Thalictrum pubescens and within morphologically dioecious T. dioicum. Females of T. pubescens produce flowers having stamens and pistils, appearing hermaphroditic. Genetic correlations were estimated as family-mean correlations among paternal half-sib families. Positive phenotypic and genetic correlations between parts of the same reproductive organs, as the anther and filament of the stamen, indicate developmental associations between these traits in both species. Negative genetic correlations were detected between pistil number and size of reproductive organs in T. dioicum and showed the same direction, but not significance, in T. pubescens. There was a negative phenotypic correlation between the number of stamens and the number of pistils within female flowers of T. pubescens. Within T. pubescens, there was a positive genetic correlation between the number of stamens in males and the number of pistils in females, indicating that floral evolution in males and females may not be independent in this species.

Magnoliopsida↗

PubMed2002

Thromboplastin-thrombomodulin-mediated time and serum folate levels are genetically correlated with the risk of thromboembolic disease: results from the GAIT project.

The GAIT (Genetic Analysis of Idiopathic Thrombophilia) Project is a family-based study dedicated to elucidating the genetic basis of hemostasis-related phenotypes and thrombosis risk. In this paper, we have examined several lesser-studied hemostasis-related phenotypes in the 21 GAIT families: levels of vitamin B 12, serum folate, whole blood folate, alpha2-antiplasmin, prekallikrein, beta2-glycoprotein I, soluble P-selectin, factor XIII A and B subunits and a new coagulation measurement based on thromboplastin time in the presence or absence of thrombomodulin. Using the variance component method, we estimated the relative contributions of genetic and environmental influences on these phenotypes. In addition, we calculated the genetic correlations between thrombosis risk and each of these phenotypes. All 12 phenotypes showed significant genetic contributions with genes accounting for 22% to 78% of the variance after correction for covariate effects. Four phenotypes (three traits involving thromboplastin-thrombomodulin mediated coagulation time and serum folate) exhibited significant genetic correlations with thrombosis. Thus, some of the genes that influence quantitative variation in these physiological phenotypes also influence the risk of thrombosis. The high heritabilities and significant genetic correlations between thrombosis and some risk factors suggest that joint consideration of correlated quantitative phenotypes will aid in identifying susceptibility genes.

Adult↗

PubMed2004

Genetic correlations among texture characteristics in the human iris.

PURPOSE: To estimate the magnitude of genetic correlations among five general textural characteristics of the human iris. METHODS: Color photographs of iris were available from 100 monozygotic and 99 dizygotic twin pairs. Comparative scales were constructed based on ratings of the subjects' left iris. To explore the genetic and environmental covariation among frequency of Fuchs' crypts, frequency of pigment dots, iris color, the extension, and distinction of Wolfflin nodules, and contraction furrows, a structural equation model with Cholesky decomposition was applied to variance-covariance matrices for monozygotic (MZ) and dizygotic (DZ) pairs. RESULTS: Significant genetic correlations fell between -0.22 and 0.44 and accounted almost entirely for the phenotypic correlations among the iris characteristics. No evidence for individual specific environmental effects in common to the characteristics was found. CONCLUSIONS: The modest genetic correlations indicate that there is little overlap in the genetic influence for these characteristics. Candidate genes with embryological and histological expression patterns in the eye could potentially influence the iris characteristics' variability.

Adolescent↗

PubMedDate not supplied

Validation of an approximate approach to compute genetic correlations between longevity and linear traits.

The estimation of genetic correlations between a nonlinear trait such as longevity and linear traits is computationally difficult on large datasets. A two-step approach was proposed and was checked via simulation. First, univariate analyses were performed to get genetic variance estimates and to compute pseudo-records and their associated weights. These pseudo-records were virtual performances free of all environmental effects that can be used in a BLUP animal model, leading to the same breeding values as in the (possibly nonlinear) initial analyses. By combining these pseudo-records in a multiple trait model and fixing the genetic and residual variances to their values computed during the first step, we obtained correlation estimates by AI-REML and approximate MT-BLUP predicted breeding values that blend direct and indirect information on longevity. Mean genetic correlations and reliabilities obtained on simulated data confirmed the suitability of this approach in a wide range of situations. When nonzero residual correlations exist between traits, a sire model gave nearly unbiased estimates of genetic correlations, while the animal model estimates were biased upwards. Finally, when an incorrect genetic trend was simulated to lead to biased pseudo-records, a joint analysis including a time effect could adequately correct for this bias.

Longevity↗

PubMed2006

Genetic correlation between heifer pregnancy and scrotal circumference measured at 15 and 18 months of age in Nellore cattle.

Data of pregnancy diagnosis from 24,945 Nellore heifers, raised under tropical conditions in Brazil and exposed to breeding at about 14 months of age, were analyzed simultaneously with 13,742 (analysis 1), 36,091 (analysis 2), 8,405 (analysis 3), and 8,405 (analysis 4) scrotal circumference (SC) records of contemporary young bulls in order to estimate heritability (h(2)) for yearling heifer pregnancy (HP) and for SC measured at around 15 (SC15) and 18 (SC18) months of age and to estimate genetic correlation between HP and SC15 (SC18). Heifer pregnancy was considered as a categorical trait, with the value 1 (success) assigned to heifers that were detected as pregnant by rectal palpation approximately 60 days after the end of a 90-day breeding season and the value 0 (failure) otherwise. In analyses 1 and 3, SC was measured at around 15 months of age and in analysis 2 and 4 it was measured at around 18 months of age. Only 8,848 animals from datasets 1 and 2 were common in both files, which means the same animals measured at different ages. Datasets used in analyses 3 and 4 included the same animals, measured at 15 and at 18 months of age, respectively. Heritability estimates for HP were similar in all analyses, with values ranging from 0.66 +/- 0.08 to 0.67 +/- 0.008. For SC15, the estimates were 0.57 +/- 0.05 in analysis 1 and 0.60 +/- 0.07 in analysis 3. For SC18, the estimates were 0.53 +/- 0.03 in analysis 2 and 0.64 +/- 0.06 in analysis 4. The estimates of genetic correlation between HP and SC15 were 0.15 +/- 0.10 in analysis 1 and 0.11 +/- 0.11 in analysis 3. For the correlation between HP and SC18, the values were 0.27 +/- 0.10 in analysis 2 and 0.16 +/- 0.11 in analysis 4. Based on standard errors and confidence intervals, the best heritability and genetic correlation estimates were obtained from analysis 2, which included more data and a better pedigree structure. Pearson correlation between HP and SC breeding values was similar to the genetic correlation estimates obtained from two-trait models, when all animals in the pedigree file were considered for its calculation. If only sires were considered for the calculation, Pearson correlation was higher but the pattern was the same as from two-trait analyses. The high heritability estimates obtained in the present study confirm that expected progeny difference (EPD) for HP can be used to select bulls for the production of precocious daughters and that the low genetic correlation between SC and HP indicates a greater efficacy of selection based on heifer pregnancy EPD than of selection based on scrotal circumference EPD. The results of the present study, although not conclusive, indicate that SC measured at around SC18 would have a higher genetic correlation with HP than would SC measured at around SC15.

Age Factors↗

PubMed1996

Common genetic determinants of the ataxic and hypothermic effects of ethanol in BXD/Ty recombinant inbred mice: genetic correlations and quantitative trait loci.

Sensitivity and tolerance to ethanol-induced ataxia and hypothermia are determined in part by genetic factors; some genes that affect one of these traits may affect others as well. To test this general hypothesis, we examined hypothermia and two tests of ataxia in the C57BL/6J and DBA/2J inbred mouse stains and in 18 to 25 of their recombinant inbred strains. Genetic correlations among strain mean responses revealed strong positive associations of genetic origin between sensitivity and tolerance for each of the three responses. Furthermore, tolerance to grid test ataxia and tolerance to hypothermia were positively associated. Sensitivity scores across the three responses were uncorrelated. The second method employed to assess genetic correlation was to examine the pattern of genetic locations of quantitative trait loci (QTLs) provisionally identified using genetic mapping procedures. This method identified 3 to 14 QTLs associated with each trait. Within each response, a number of these associations were in common for measures of sensitivity and tolerance; this suggests the existence of several specific genes that exert pleiotropic effects on sensitivity and tolerance. In a result consistent with the analyses of genetic correlations, there was modest evidence for QTLs associated across measures. Some QTLs associated with multiple traits mapped to chromosomal regions where candidate genes (e.g., genes for neurotransmitter receptors) have been mapped. In summary, the analyses presented suggest modest commonality of genetic influence on tolerance to some measures of ataxia and hypothermia, and they strongly support previous data indicating that sensitivity and tolerance to specific effects of ethanol share common genetic determinants.

Animals↗

PubMed2005

Estimates of genetic correlations between days to calving and reproductive and weight traits in Nelore cattle.

Data comprising 53,181 calving records were analyzed to estimate the genetic correlation between days to calving (DC), and days to first calving (DFC), and the following traits: scrotal circumference (SC), age at first calving (AFC), and weight adjusted for 550 d of age (W550) in a Nelore herd. (Co)variance components were estimated using the REML method fitting bivariate animal models. The fixed effects considered for DC were contemporary group, month of last calving, and age at breeding season (linear and quadratic effects). Contemporary groups were composed by herd, year, season, and management group at birth; herd and management group at weaning; herd, season, and management group at mating; and sex of calf and mating type (multiple sires, single sire, or AI). In DFC analysis, the same fixed effects were considered excluding the month of last calving. For DC, a repeatability animal model was applied. Noncalvers were not considered in analyses because an attempt to include them, attributing a penalty, did not improve the identification of genetic differences between animals. Heritability estimates ranged from 0.04 to 0.06 for DC, from 0.06 to 0.13 for DFC, from 0.42 to 0.44 for SC, from 0.06 to 0.08 for AFC, and was 0.30 for W550. The genetic correlation estimated between DC and SC was low and negative (-0.10), between DC and AFC was high and positive (0.76), and between DC and W550 was almost null (0.07). Similar results were found for genetic correlation estimates between DFC and SC (-0.14), AFC (0.94), and W550 (-0.02). The genetic correlation estimates indicate that the use of DC in the selection of beef cattle may promote favorable correlated responses to age at first mating and, consequently, higher gains in sexual precocity can be expected.

Age Factors↗

PubMed2005

Milk urea nitrogen concentration: heritability and genetic correlations with reproductive performance and disease.

The objectives of this study were to estimate the heritability of milk urea nitrogen (MUN) concentration and describe the genetic relationship between MUN and reproductive performance and between MUN and diseases in Holsteins. Dairy Records Management Systems (Raleigh, NC) provided lactation data. The Danish Agricultural Advisory Center provided breeding value estimates for diseases. Infrared (IR) and wet chemistry (WC) data were analyzed separately. Heritabilities and genetic correlations for 2 different measures of MUN and reproductive performance were estimated with an animal model using ASREML. Heritabilities for MUN were estimated using all lactations combined (lactations 1 through 5) and separately for first lactation and second lactation. Genetic correlations with reproduction and health were estimated separately for parities 1 and 2. Herd-test-day or herd-year-season along with age at calving and days in milk were included as fixed effects in all models. Heritability estimates for all lactations combined were 0.15 for WC MUN and 0.22 for IR MUN. Genetic correlations between WC MUN and 2 measures of reproductive performance, days to first service, and first service conception were not different from zero. In contrast, the genetic correlation between WC MUN and days open of 0.21 in first lactation and 0.41 in second lactation indicated that higher WC MUN values were associated with increased days open. Correlations among estimated breeding values for MUN and estimated breeding values for Danish diseases identified no significant relationships. Although the results of this study indicate that heritable variation for MUN exists, the inability to identify significant genetic relationships with several measures of disease or reproductive performance appears to limit the value of MUN in selection for disease resistance and improved reproduction.

Animals↗

PubMed2006

A comparison of methods to estimate cross-environment genetic correlations.

Advanced techniques for quantitative genetic parameter estimation may not always be necessary to answer broad genetic questions. However, simpler methods are often biased, and the extent of this determines their usefulness. In this study we compare family mean correlations to least squares and restricted error maximum likelihood (REML) variance component approaches to estimating cross-environment genetic correlations. We analysed empirical data from studies where both types of estimates were made, and from studies in our own laboratories. We found that the agreement between estimates was better when full-sib rather than half-sib estimates of cross-environment genetic correlations were used and when mean family size increased. We also note biases in REML estimation that may be especially important when testing to see if correlations differ from 0 or 1. We conclude that correlations calculated from family means can be used to test for the presence of genetic correlations across environments, which is sufficient for some research questions. Variance component approaches should be used when parameter estimation is the objective, or if the goal is anything other than determining broad patterns.

Analysis of Variance↗

PubMed2001

Disease-induced variability of genetic correlations: ascites in broilers as a case study.

Breeding against a production disease is complicated by multiple relationships between productivity, disease, and environment. Ascites in broilers is such a disease. The combination of the reasonably well understood etiology (a physiological/pathological cascade due to inadequate oxygen supply) and the practical relevance makes ascites a relevant case for demonstrating and partly revealing these complex relationships. Chickens (n = 2,788) were tested in an ascites-challenging (cold) environment. Genetic analysis of mortality and pathology in combination with performance and physiological traits (especially blood gas traits) revealed ample opportunities for selection against ascites expression. The genetic correlation structure indicated that different mortality traits and pathology traits roughly represent one common characteristic. Direct selection against pathology is more effective than selection on the basis of growth or blood gas traits. The observed negative correlation (-0.26) between productivity and ascites was unexpected. From the etiology of ascites (inadequate supply of oxygen relative to the demand), a positive (unfavorable) correlation was expected. To demonstrate that the actual disease occurrence caused this apparent contradiction, the data from the undiseased subpopulation were reanalyzed. In the undiseased subpopulation, the genetic correlation between productivity and ascites was positive (0.29). This discrepancy was confirmed by comparing regression of ascites expression on actual performance with regression of ascites on independently assessed performance breeding values. The lability of the genetic correlation was explained from complex interactions between productivity, disease susceptibility, and actual occurrence of the disease. The revealed mechanism can be generalized to other production-related diseases and results in systematically lower genetic correlations between disease and productivity. It was inferred that genetic correlations between productivity and such diseases will always be prone to the demonstrated environmental sensitivity, which complicates index selection against production-related diseases.

Animals↗