Journal articles: 'Genetic and Phenotypic Correlations'

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Via, Sara, and Russell Lande. "Evolution of genetic variability in a spatially heterogeneous environment: effects of genotype–environment interaction." Genetical Research 49, no. 2 (April 1987): 147–56. http://dx.doi.org/10.1017/s001667230002694x.

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SummaryClassical population genetic models show that disruptive selection in a spatially variable environment can maintain genetic variation. We present quantitative genetic models for the effects of disruptive selection between environments on the genetic covariance structure of a polygenic trait. Our models suggest that disruptive selection usually does not alter the equilibrium genetic variance, although transient changes are predicted. We view a quantitative character as a set of character states, each expressed in one environment. The genetic correlation between character states expressed in different environments strongly affects the evolution of the genetic variability. (1) If the genetic correlation between character states is not ± 1, then the mean phenotype expressed in each environment will eventually attain the optimum value for that environment; this is the evolution of phenotypic plasticity (Via & Lande, 1985). At the joint phenotypic optimum, there is no disruptive selection between environments and thus no increase in the equilibrium genetic variability over that maintained by a balance between mutation and stabilizing selection within each environment. (2) If, however, the genetic correlation between character states is ± 1, the mean phenotype will not evolve to the joint phenotypic optimum and a persistent force of disruptive selection between environments will increase the equilibrium genetic variance. (3) Numerical analyses of the dynamic equations indicate that the mean phenotype can usually be perturbed several phenotypic standard deviations from the optimum without producing transient changes of more than a few per cent in the genetic variances or correlations. It may thus be reasonable to assume a roughly constant covariance structure during phenotypic evolution unless genetic correlations among character states are extremely high or populations are frequently perturbed. (4) Transient changes in the genetic correlations between character states resulting from disruptive selection act to constrain the evolution of the mean phenotype rather than to facilitate it.

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Feldman, Marcus W., Freddy B. Christiansen, and Sarah P. Otto. "Gene-culture co-evolution: teaching, learning, and correlations between relatives." Israel Journal of Ecology and Evolution 59, no. 2 (May 18, 2013): 72–91. http://dx.doi.org/10.1080/15659801.2013.853435.

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Heritability, the fraction of phenotypic variance attributable to the action of genes, is usually derived from a linear statistical partition of variance. In this paper we study a dichotomous phenotype whose transmission from parents to offspring depends on the parents’ phenotypes and the offspring’s genotype. Each individual is then represented as a phenogenotype. We derive expressions for each component of phenotypic variance and for covariances between relatives of various degrees. The resulting heritability estimates vary with the rates of phenotypic transmission as well as with the genetic contribution to the phenotype. Assortative mating by phenotype in parents is also shown to contribute to the correlations between relatives. In addition, we show that the frequency of alleles at genes affecting the phenotypes strongly affects standard heritability measures. This is important because for most complex traits these allele frequencies cannot be ascertained.

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Vaissiere, James, Jackson G. Thorp, Jue-Sheng Ong, Alfredo Ortega-Alonso, and Eske M. Derks. "Exploring Phenotypic and Genetic Overlap Between Cannabis Use and Schizotypy." Twin Research and Human Genetics 23, no. 4 (August 2020): 221–27. http://dx.doi.org/10.1017/thg.2020.68.

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AbstractThere is a well-established relationship between cannabis use and psychosis, although the exact nature of this relationship is not fully understood. Recent studies have observed significant genetic overlap between a diagnosis of schizophrenia and lifetime cannabis use. Expanding on this work, the current study aimed to examine whether genetic overlap also occurs for subclinical psychosis (schizotypy) and cannabis use, as well as examining the phenotypic association between the traits. Phenotypic correlations were calculated for a variety of schizotypy and cannabis phenotypes in the UK Biobank (UKB), and single nucleotide polymorphism (SNP)-based heritability estimates and genetic correlations were calculated for these UKB phenotypes as well as for several other variables taken from recent genomewide association studies. Positive phenotypic correlations were observed between 11 out of 12 pairs of the cannabis use and schizotypy phenotypes (correlation range .05–.18), indicating a robust association between increased symptoms of schizotypy and cannabis use. SNP-based heritability estimates for two schizotypy phenotypes remained significant after multiple testing correction: social anhedonia (h2SNP = .08, SE = .02, N = 4025) and ever seen an unreal vision (h2SNP = .35, SE = .10, N = 150,717). Finally, one significant genetic correlation was observed between schizotypy and cannabis use, a negative correlation between social anhedonia and number of times used cannabis (rg = −.30, p = .012). The current study suggests the relationship between cannabis use and psychosis is also seen in subclinical symptoms of psychosis, but further research with larger samples is needed to determine the biological mechanisms underlying this association.

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Cheverud, James M. "A Comparison of Genetic and Phenotypic Correlations." Evolution 42, no. 5 (September 1988): 958. http://dx.doi.org/10.2307/2408911.

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Cheverud, James M. "A COMPARISON OF GENETIC AND PHENOTYPIC CORRELATIONS." Evolution 42, no. 5 (September 1988): 958–68. http://dx.doi.org/10.1111/j.1558-5646.1988.tb02514.x.

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Winship, I. M., J. M. Connor, and P. H. Beighton. "Genetic heterogeneity in tuberous sclerosis: phenotypic correlations." Journal of Medical Genetics 27, no. 7 (July 1, 1990): 418–21. http://dx.doi.org/10.1136/jmg.27.7.418.

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Schwartz, Christopher J., and Timothy M. D'Alfonso. "Breast cancers with special genetic-phenotypic correlations." Diagnostic Histopathology 27, no. 4 (April 2021): 155–63. http://dx.doi.org/10.1016/j.mpdhp.2021.01.003.

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Minica, Camelia C., Dorret I. Boomsma, Sophie van der Sluis, and Conor V. Dolan. "Genetic Association in Multivariate Phenotypic Data: Power in Five Models." Twin Research and Human Genetics 13, no. 6 (December 1, 2010): 525–43. http://dx.doi.org/10.1375/twin.13.6.525.

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This article concerns the power of various data analytic strategies to detect the effect of a single genetic variant (GV) in multivariate data. We simulated exactly fitting monozygotic and dizygotic phenotypic data according to single and two common factor models, and simplex models. We calculated the power to detect the GV in twin 1 data in an ANOVA of phenotypic sum scores, in a MANOVA, and in exploratory factor analysis (EFA), in which the common factors are regressed on the genetic variant. We also report power in the full twin model, and power of the single phenotype ANOVA. The results indicate that (1) if the GV affects all phenotypes, the sum score ANOVA and the EFA are most powerful, while the MANOVA is less powerful. Increasing phenotypic correlations further decreases the power of the MANOVA; and (2) if the GV affects only a subset of the phenotypes, the EFA or the MANOVA are most powerful, while sum score ANOVA is less powerful. In this case, an increase in phenotypic correlations may enhance the power of MANOVA and EFA. If the effect of the GV is modeled directly on the phenotypes in the EFA, the power of the EFA is approximately equal to the power of the MANOVA.

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Cheverud, James M., and Larry J. Leamy. "Quantitative genetics and the evolution of ontogeny. III. Ontogenetic changes in correlation structure among live-body traits in randombred mice." Genetical Research 46, no. 3 (December 1985): 325–35. http://dx.doi.org/10.1017/s0016672300022813.

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SUMMARYOntogenetic series of phenotypic, additive genetic, maternal and environmental correlation matrices are presented and interpreted in the light of recent models for the Ontogenetic origin and variation in correlation between traits. A total of 432 mice from 108 full-sib families raised in a cross-fostering design were used to estimate the various components of phenotypic correlation for five live-body traits at eight ages. The level of genetic and phenotypic correlation decreased with age, while levels of maternal and environmental correlation remained more or less constant. Genetic correlations probably decreased due to compensatory growth. Phenotypic correlations decreased primarily due to the relative decrease in importance of highly correlated maternal effects and consequent increase in poorly correlated environmental effects as portions of phenotypic variation. The effect of compensatory growth on genetic correlation was also responsible for a portion of the decline in phenotypic correlation. Phenotypic correlation patterns remained constant over the ages studied here. It also seems likely the genetic, maternal and environmental correlation patterns do not change with age for the characters analysed.

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HADFIELD, J. D., A. NUTALL, D. OSORIO, and I. P. F. OWENS. "Testing the phenotypic gambit: phenotypic, genetic and environmental correlations of colour." Journal of Evolutionary Biology 20, no. 2 (March 2007): 549–57. http://dx.doi.org/10.1111/j.1420-9101.2006.01262.x.

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Mazer, Susan J. "Family mean correlations among fitness components in wild radish: controlling for maternal effects on seed weight." Canadian Journal of Botany 67, no. 6 (June 1, 1989): 1890–97. http://dx.doi.org/10.1139/b89-240.

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Qualitative estimates of genetic associations among life-history and fitness components are reported for 30 sibships (or families) in a common garden population of Raphanus raphanistrum L. (Brassicaceae: wild radish). Genetic associations are detected in a qualitative way when correlation coefficients among family means are highly significant. In this study, correlation coefficients among family means are compared with phenotypic correlation coefficients and to each other to address three questions: (i) Do strong genetic trade-offs among fitness components exist in wild radish under experimental conditions? (ii) Do qualitative estimates of genetic associations differ from phenotypic correlations? and (iii) Since seed weight is strongly phenotypically correlated with many components of plant performance and since families differ in seed weight because of strong maternal environmental (nongenetic) effects, does controlling for seed weight affect the correlations among family means? Many heritable fitness components were positively correlated among families; however, strong positive phenotypic correlation coefficients were much more common than strong positive family-mean correlation coefficients. No strong negative genetic associations were detected. The tendency for phenotypic correlations to be more positive than family mean correlations is consistent with the expectation that environmental variation generates positive correlations among characters, masking genetically based trade-offs. Partitioning out the effect of seed weight had only a small effect on the magnitude of the among-family correlation coefficients.

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Riska, B., T. Prout, and M. Turelli. "Laboratory estimates of heritabilities and genetic correlations in nature." Genetics 123, no. 4 (December 1, 1989): 865–71. http://dx.doi.org/10.1093/genetics/123.4.865.

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Abstract A lower bound on heritability in a natural environment can be determined from the regression of offspring raised in the laboratory on parents raised in nature. An estimate of additive genetic variance in the laboratory is also required. The estimated lower bounds on heritabilities can sometimes be used to demonstrate a significant genetic correlation between two traits in nature, if their genetic and phenotypic correlations in nature have the same sign, and if sample sizes are large, and heritabilities and phenotypic and genetic correlations are high.

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Gilbert, James R., James J. Cray, Amy Kreithen, Mary L. Marazita, Gregory M. Cooper, Joseph E. Losee, Michael I. Siegel, and Mark P. Mooney. "Genetic Homozygosity and Phenotypic Variability in Craniosynostotic Rabbits." Cleft Palate-Craniofacial Journal 54, no. 1 (January 2017): 94–99. http://dx.doi.org/10.1597/15-226.

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Background Craniosynostosis ranges in severity from single suture involvement with prenatal onset to multiple suture involvement with postnatal onset. The present study was designed to test the hypothesis that increasing homozygosity may be responsible for more severe phenotypic expression by examining the relationship between inbreeding and phenotypic expression in synostotic rabbits. Methods Data were obtained from 173 litters and 209 rabbits with familial craniosynostosis. Five distinct phenotypes were identified (normal n = 62; unicoronal delayed onset synostosis (DOS) n = 47; bicoronal DOS n - 21; unicoronal early onset synostosis (EOS) n - 26, and bicoronal EOS n = 53). Wright's coefficients of inbreeding (CI) were calculated using CompuPed software. Radiographs were taken at 10, 25, 42, 84, and 126 days of age to assess coronal suture, craniofacial, and skeletal growth. The relationship between CI and growth data was assessed using correlation coefficients. Results Mean CIs ranged from 15.68 (±2.22) in normal rabbits to 25.89 (±5.03) in bicoronal DOS, to 36.29 (±2.10) in unicoronal EOS to 42.85 (±2.10) in bicoronal EOS rabbits. Significant differences were noted among groups (F - 11.48; P < .001). Significant negative correlations were noted between CI and sutural and craniofacial growth at 25 (r = -.45, P < .001; and r = -.66, P < .001) through 126 (r = -.40, P < .001 and r = -.46, P < .001) days of age. Conclusions While the synostotic phenotype is inherited in an autosomal dominant fashion in these rabbits, increasing homozygosity is associated with more severely affected phenotypes. These findings suggest that an accumulation of additional, modifier genes may determine the severity of the synostotic phenotype in rabbits.

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HASSAN, W. A., N. I. DIM, O. A. OSINOWO, and B. Y. ABUBAKAR. "GENETIC AND PHENOTYPIC CORRELATIONS FOR BODY WEIGHTS IN YANKASA SHEEP." Nigerian Journal of Animal Production 18 (January 12, 2021): 12–18. http://dx.doi.org/10.51791/njap.v18i.1931.

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Using paternal half-sib (PHS) analysis, coefficients of genetic and phenotypic correlations be- tween body weights of Yankasa lambs at birth, weaning (three months), six months, nine months and one year of age were estimate. The highest genetic correlation coefficient of 0.33 was obtained between birth and yearling weight. Six- month weight had very low and negative genetic correlation with yearling weight (-0.04). Phenotypic correlation coefficients for the various body weights pairs were positive and mostly of medium magnitude (0.12 -0.47).

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Pigliucci, Massimo. "Modelling phenotypic plasticity. II. Do genetic correlations matter?" Heredity 77, no. 5 (November 1996): 453–60. http://dx.doi.org/10.1038/hdy.1996.171.

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Stearns, Steve, Gerdien de Jong, and Bob Newman. "The effects of phenotypic plasticity on genetic correlations." Trends in Ecology & Evolution 6, no. 4 (April 1991): 122–26. http://dx.doi.org/10.1016/0169-5347(91)90090-k.

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Scheiner, Samuel M., Roberta L. Caplan, and Richard F. Lyman. "The genetics of phenotypic plasticity. III. Genetic correlations and fluctuating asymmetries." Journal of Evolutionary Biology 4, no. 1 (January 1991): 51–68. http://dx.doi.org/10.1046/j.1420-9101.1991.4010051.x.

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Almasy, Laura, John Blangero, William Stone, Montse Borrell, Teresa Urrutia, José Mateo, Jordi Fontcuberta, and Juan Carlos Souto. "Genetic Regulation of Plasma Levels of Vitamin K-dependent Proteins Involved in Hemostasis." Thrombosis and Haemostasis 85, no. 01 (2001): 88–92. http://dx.doi.org/10.1055/s-0037-1612909.

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SummaryVitamin K-dependent proteins play a critical role in hemostasis. We have analysed the genetic and environmental correlations between measures of several vitamin K-dependent proteins in 21 Spanish extended families, including 397 individuals. Plasma functional levels of factors II, VII, IX, X, protein C and functional protein S were assayed in an automated coagulometer. Antigenic levels of total and free protein S were measured using an ELISA method. A maximum likelihood-based covariance decomposition analysis was used to assess the heritability of each trait and the genetic and environmental correlations between all possible pairs. All of the plasma levels had a significant genetic component (heritability) ranging from 22% to 52% of the phenotypic variance. Among the 28 possible pairs of genetic correlations, 18 were significant at a level of p <0.05 and six exhibited a p-value between 0.05 and 0.10. Positive environmental correlation was observed for 25 of the pairs (p <0.05). We conclude that genetic effects account for a large proportion of the observed phenotypic variation in vitamin K-dependent proteins. Some of the genes appear to pleiotropically influence all of these traits, since most pairs of phenotypes exhibit significant genetic correlation. However, since these phenotypes show a high degree of environmental correlation, it is also likely that the same environmental factors influence them co-jointly.

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Molenaar, Peter C. M. "Estimating the actual subject-specific genetic correlations in behavior genetics." Behavioral and Brain Sciences 35, no. 5 (October 2012): 373–74. http://dx.doi.org/10.1017/s0140525x12001069.

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AbstractGeneralization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.

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Boujenane, I., M. Kerfal, and M. Khallouk. "Genetic and phenotypic parameters for litter traits of D'Man ewes." Animal Science 52, no. 1 (February 1991): 127–32. http://dx.doi.org/10.1017/s0003356100005754.

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ABSTRACTA total of 1754 records for litter traits of 458 D'man ewes sired by more than 45 rams were analysed to estimate repeatability, heritability and genetic and phenotypic correlations. Repeatability estimated by the intraclass correlation method was 0·11, 0·11, 0·12 and 0·15 for litter sizes at birth and at weaning and litter weights at birth and at weaning, respectively. Paternal half-sib estimates of heritability were 0·09 (s.e. 0·06), 0·04 (s.e. 0·05), 0·15 (s.e. 0·07) and 0·08 (s.e. 0·05), respectively. Genetic correlations among the traits were all positive and varied from 0·17 to 0·72, whereas phenotypic correlations ranged from 0·68 to 0·86.

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Petrovic, M. P., V. Caro-Petrovic, D. Ruzic-Muslic, Z. Ilic, Z. Spasic, J. Stojkovic, and M. Milenkovic. "Genetic and phenotypic aspects of the body measured traits in merinolandschaf breed of sheep." Biotehnologija u stocarstvu 28, no. 4 (2012): 733–41. http://dx.doi.org/10.2298/bah1204733p.

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Merinolandschaf sheep breed was used to estimate relationship between the next traits: Body weight of adult ewes (BW), Height to withers (HW), Body length (BL), Girth of Chest (GC), Rump Width (RW), Body weight of lambs at birth (BWB), Body weight of lambs at weaning (BWW). The collected data were from 750 sheep and their lambs during the period of three year. Estimates of means and standard errors for linear body measures and body weight of adult ewes and lambs, were obtained using the software program SPSS (2006). To estimate genetic and phenotypic correlations of observed traits, the ASREML program was used. Research has shown that genetic correlations between BW and all body measures of dams, ranging from 0.728 (BW-GC) to 0.976 (BW-HW). Genetic correlation between body measures of dams have also been positive and ranged in the interval from 0.873 (HW-GC) to 0.999 (BL-GC). Values for phenotypic correlations were lower compared with the genetic and the range varied from 0.183 (RW-BWB) to 0.421 (GC-BWW). The weaker phenotype correlations can be interpreted as play of more complex genetic and residual factors.

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Hur, Yoon-Mi, Hee-Jeong Jin, and Siwoo Lee. "Etiologies of the Relationships Among Body Mass Index and Cold-Heat Patterns: A Twin Study." Twin Research and Human Genetics 21, no. 3 (April 30, 2018): 233–38. http://dx.doi.org/10.1017/thg.2018.18.

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The phenotypic relationships between body mass index (BMI) and cold-heat patterns have been frequently reported, but the etiology of these relationships remains unknown. We previously demonstrated that the cold pattern (CP) and the heat pattern (HP) were heritable traits. In the present study, we explored underlying genetic and environmental structures of the relationships among BMI and the CP and the HP. Twins (N = 1,752) drawn from the South Korean twin registry completed a cold-heat pattern questionnaire via a telephone interview. The phenotypic correlations among the three phenotypes were moderate but significant. Cross-twin, cross-trait correlations among BMI and the CP and the HP were consistently greater in monozygotic than in dizygotic twins, suggesting the presence of genetic effects on the relationships between BMI and the two patterns. A trivariate Cholesky model was applied to the raw data. The results indicated that the phenotypic relationship between the HP and BMI was completely determined by common genetic influences, while the relationship between the CP and BMI was explained by both common genetic and common individual-specific environmental influences. The genetic correlation between the HP and the CP was not significant, suggesting that the two patterns may be genetically independent from each other. Genetic correlations were 0.31 between the HP and BMI, and -0.22 between the CP and BMI. The individual-specific environmental correlation was -0.22 between HP and CP, and between CP and BMI.

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Grange, Thomas, Mélodie Aubart, Maud Langeois, Louise Benarroch, Pauline Arnaud, Olivier Milleron, Ludivine Eliahou, et al. "Quantifying the Genetic Basis of Marfan Syndrome Clinical Variability." Genes 11, no. 5 (May 20, 2020): 574. http://dx.doi.org/10.3390/genes11050574.

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Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder with considerable inter- and intra-familial clinical variability. The contribution of inherited modifiers to variability has not been quantified. We analyzed the distribution of 23 clinical features in 1306 well-phenotyped MFS patients carrying FBN1 mutations. We found strong correlations between features within the same system (i.e., ophthalmology vs. skeletal vs. cardiovascular) suggesting common underlying determinants, while features belonging to different systems were largely uncorrelated. We adapted a classical quantitative genetics model to estimate the heritability of each clinical feature from phenotypic correlations between relatives. Most clinical features showed strong familial aggregation and high heritability. We found a significant contribution by the major locus on the phenotypic variance only for ectopia lentis using a new strategy. Finally, we found evidence for the “Carter effect” in the MFS cardiovascular phenotype, which supports a polygenic model for MFS cardiovascular variability and indicates additional risk for children of MFS mothers with an aortic event. Our results demonstrate that an important part of the phenotypic variability in MFS is under the control of inherited modifiers, widely shared between features within the same system, but not among different systems. Further research must be performed to identify genetic modifiers of MFS severity.

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Mrode, R. A., and G. J. T. Swanson. "Genetic and phenotypic relationships between conformation and production traits in Ayrshire heifers." Animal Science 58, no. 3 (June 1994): 335–38. http://dx.doi.org/10.1017/s0003356100007261.

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AbstractFirst lactation records for production traits (milk, fat and protein yields) and 17 linear type traits for 7169 Ayrshire heifers were analysed to estimate genetic parameters for type traits and to examine the relationship between type and production traits. A multivariate restricted maximum likelihood procedure fitting a sire model with sire relationships included was used for all analyses.Heritabilities for production traits were approximately 0·3 and genetic correlations among them were high (>0·84). The estimates of heritabilities for type traits were mainly low to moderate ranging from 0·04 to 0·42. Angularity (0·80), beef shape (0·49), foot angle (0·53) and stature (0·46) had higher heritabilities. Generally phenotypic correlations among type traits were lower than the genetic correlations. The highest negative genetic correlation was between rear legs side and rear legs rear (-0·95) and the highest positive correlation between chest width and beef shape (0·93).Genetic correlations between type and production were low to moderate and were similar for milk, fat and protein yields. The genetic correlations between the production traits and chest width, udder depth and beef shape were negative but were positive between production and angularity, rear udder width and teat placement side.

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Biton, Anne, Nicolas Traut, Jean-Baptiste Poline, Benjamin S. Aribisala, Mark E. Bastin, Robin Bülow, Simon R. Cox, et al. "Polygenic Architecture of Human Neuroanatomical Diversity." Cerebral Cortex 30, no. 4 (February 28, 2020): 2307–20. http://dx.doi.org/10.1093/cercor/bhz241.

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Abstract We analyzed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26 000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r ~ 0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (~51%) captured ~1.5 times more genetic variance than the rest, and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF <5% captured <one fourth of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG ~ 0.45. Genetic correlations were similar to phenotypic and environmental correlations; however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available athttps://github.com/neuroanatomy/genomic-architecture.

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Moore, K. L., D. J. Johnston, H.-U. Graser, and R. Herd. "Genetic and phenotypic relationships between insulin-like growth factor-I (IGF-I) and net feed intake, fat, and growth traits in Angus beef cattle." Australian Journal of Agricultural Research 56, no. 3 (2005): 211. http://dx.doi.org/10.1071/ar04248.

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Insulin-like growth factor-I (IGF-I) concentration measured in the blood plasma of 6520 seedstock Angus beef cattle (3622 bulls and 2898 heifers) from eastern Australia between 2002 and 2004 was used to estimate the heritability of IGF-I and phenotypic and genetic correlations with net feed intake (NFI) and other production traits. The average concentration of IGF-I was 314 ng/mL measured at the average age of 242 days. A moderate heritability of 0.35 was estimated for IGF-I. IGF-I was further defined as being measured either at, or prior to, weaning (average age of 201 days) or post-weaning (average age 310 days). The genetic correlation between IGF-I recorded at the different ages was 1.0 ± 0.04. IGF-I and NFI were found to have a genetic correlation of 0.41 ± 0.21. IGF-I had positive genetic correlations of 0.22 ± 0.14, 0.19 ± 0.14, and 0.26 ± 0.15 with ultrasound-scanned subcutaneous fat depth at the rump (P8) and 12/13th rib (RIB) sites and intramuscular fat % (IMF), respectively. Corresponding phenotypic correlations were 0.14, 0.13, and 0.12, respectively, for P8, RIB, and IMF. IGF-I had low to moderate negative genetic correlations with growth traits. Direct genetic correlations for IGF-I of –0.22 ± 0.08, –0.17 ± 0.09 and –0.10 ± 0.14 were estimated with birth (BWT), 200-day (WT200), and 400-day (WT400) weights, respectively. Genetic correlations between the direct component of IGF-I and maternal components of BWT and WT200 were 0.15 ± 0.13 and 0.31 ± 0.11, respectively. Phenotypic correlations of the direct component of IGF-I with the direct components of BWT, WT200, and WT400 were –0.10, 0.06, and 0.16, respectively. Ultrasound-scanned eye muscle area (EMA) and IGF-I had genetic and phenotypic correlations of –0.22 ± 0.15 and 0.13, respectively. This study showed that IGF-I is heritable and genetically correlated with important production traits. The genetic correlations indicate that selection for lower IGF-I concentrations would result in cattle that have lower NFI (i.e. more feed efficient), are leaner, with increased growth, and possibly decreased maternal weaning weight.

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Kominakis, A. P. "Phenotypic correlations as substitutes to genetic correlations in dairy sheep and goats*." Journal of Animal Breeding and Genetics 120, no. 4 (August 2003): 269–81. http://dx.doi.org/10.1046/j.1439-0388.2003.00397.x.

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Koots, Kenneth R., and John P. Gibson. "Realized Sampling Variances of Estimates of Genetic Parameters and the Difference Between Genetic and Phenotypic Correlations." Genetics 143, no. 3 (July 1, 1996): 1409–16. http://dx.doi.org/10.1093/genetics/143.3.1409.

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Abstract A data set of 1572 heritability estimates and 1015 pairs of genetic and phenotypic correlation estimates, constructed from a survey of published beef cattle genetic parameter estimates, provided a rare opportunity to study realized sampling variances of genetic parameter estimates. The distribution of both heritability estimates and genetic correlation estimates, when plotted against estimated accuracy, was consistent with random error variance being some three times the sampling variance predicted from standard formulae. This result was consistent with the observation that the variance of estimates of heritabilities and genetic correlations between populations were about four times the predicted sampling variance, suggesting few real differences in genetic parameters between populations. Except where there was a strong biological or statistical expectation of a difference, there was little evidence for differences between genetic and phenotypic correlations for most trait combinations or for differences in genetic correlations between populations. These results suggest that, even for controlled populations, estimating genetic parameters specific to a given population is less useful than commonly believed. A serendipitous discovery was that, in the standard formula for theoretical standard error of a genetic correlation estimate, the heritabilities refer to the estimated values and not, as seems generally assumed, the true population values.

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Roshanfekr, H., P. Berg, K. Mohammadi, and Mirza Mohamadi. "Genetic parameters and genetic gains for reproductive traits of Arabi sheep." Biotehnologija u stocarstvu 31, no. 1 (2015): 23–36. http://dx.doi.org/10.2298/bah1501023r.

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The current study reports, for the first time, the genetic parameters and genetic, phenotypic and environmental correlations and trends of reproductive traits in Arabi sheep. Data were collected at Animal Science Research Station of Khuzestan Ramin Agricultural and Natural Resources University (ASRSKRANRU), south-west of Iran from 2001 to 2008. Litter size at birth (LSB), litter size at weaning (LSW), litter mean weight per lamb born (LMWLB), litter mean weight per lamb weaned (LMWLW), total litter weight at birth (TLWB) and total litter weight at weaning (TLWW) averaged 1.11 lambs, 1.01 lambs, 3.83 kg, 19.43 kg, 4.16 kg and 20.12 kg, respectively. Genetic parameters and correlations were estimated with univariate and bivariate models using restricted maximum likelihood, breeding values of animals were estimated with best linear unbiased prediction (BLUP) and genetic- and phenotypic trends by regression of ewes? average breeding values and phenotypic least square means on year of birth respectively. Random effects were fitted by additive direct genetic effects and permanent environment related to the ewe as well as service sire effects, in addition to fixed effects of ewe age at lambing and lambing year. Heritability estimates of 0.05, 0.02, 0.13, 0.12, 0.04, and 0.06, and repeatability estimates of 0.08, 0.06, 0.17, 0.16, 0.14 and 0.21 for the six traits, respectively. Genetic correlations between traits varied from ?0.82 to 0.94. Phenotypic correlations were lower, ranging from ?0.33 to 0.52. Estimated annual genetic progress was very low; ?0.003 lambs for LSW and 15 g for TLWW. Annual phenotypic trend was only significant for LSW being 0.007 lambs. The study concluded that indirect selection based on total litter weight at weaning could be efficient for the traits studied.

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de Souza, Valdomiro A. B., David H. Byrne, and Jeremy F. Taylor. "Heritability, Genetic, and Phenotypic Correlations of Several Peach Traits." HortScience 30, no. 4 (July 1995): 763B—763. http://dx.doi.org/10.21273/hortsci.30.4.763b.

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Heritability estimates are useful to predict genetic progress among offspring when the parents are selected on their performance, but they also provide information about major changes in the amount and nature of genetic variability through generations. Genetic and phenotypic correlations, on the other hand, are useful for better planning of selection programs. In this research, seedlings of 39 families resulting from crosses among 27 peach [Prunus persica (L.) Batsch] cultivars and selections were evaluated for date of full bloom (DFB), date of ripening (DR), fruit period development (FDP), flower density (FD), node density (ND), fruit density (FRD), fruit weight (WT), soluble solids content (SS), apical protuberance (TIP), red skin color (BLUSH), and shape (SH) in 1993 and 1994. The data were analyzed using the mixed linear model. The best linear unbiased prediction (BLUP) was used to estimate fixed effects and predict breeding values (BV). Restricted maximum likelihood (REML) was used to estimate variance components, and a multiple-trait model to estimate genetic and phenotypic covariances between traits. The data indicates high heritability for DFB, DR, FDP, and BLUSH, intermediate heritability for WT, TIP, and SH, and low heritability for FD, ND, FRD, and SS. They also indicate year effect as a major environmental component affecting seedling performance. High correlation estimates were found between some traits, but further analysis is needed to determine their significance.

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Ortiz, R. "Genetic and phenotypic correlations in plantain-banana euploid hybrids." Plant Breeding 116, no. 5 (October 1997): 487–91. http://dx.doi.org/10.1111/j.1439-0523.1997.tb01036.x.

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Radojkovic, Dragan, Milica Petrovic, Milan Mijatovic, and Ivan Radovic. "Phenotypic and genetic correlation of fertility traits of Swedish landrace sows." Biotehnologija u stocarstvu 21, no. 3-4 (2005): 79–88. http://dx.doi.org/10.2298/bah0504079r.

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The aims of this paper were: determination of correlation between fertility traits both at phenotypic and at genetic level, determination of dependency of exsamined parameters from the analysed data size as well as determination of influence of data corrections on correlations between traits. Phenotypic correlation between litter size and weight did not confirm after correction for NWP and LWW. Between NLB and NTB phenotypic correlation was complete (from rP=0.922 to rP=0.929) and statistical very significant (P<0.01). Genetic correlation among traits were in range from low (rG=0.230, NWP:TNB) to complete (rG=1.197, cNWP:NLB). So wide range for genetic correlation was consequence of analyzed data set. Statistical significance for obtained parameters were high (P<0.01).

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Roff, Derek A. "The estimation of genetic correlations from phenotypic correlations: a test of Cheverud's conjecture." Heredity 74, no. 5 (May 1995): 481–90. http://dx.doi.org/10.1038/hdy.1995.68.

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Gwaze, D. P., K. J. Harding, R. C. Purnell, and F. E. Bridgwater. "Optimum selection age for wood density in loblolly pine." Canadian Journal of Forest Research 32, no. 8 (August 1, 2002): 1393–99. http://dx.doi.org/10.1139/x02-064.

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Genetic and phenotypic parameters for core wood density of Pinus taeda L. were estimated for ages ranging from 5 to 25 years at two sites in southern United States. Heritability estimates on an individual-tree basis for core density were lower than expected (0.200.31). Ageage genetic correlations were higher than phenotypic correlations, particularly those involving young ages. Ageage genetic correlations were high, being greater than 0.75. Ageage genetic correlations had a moderately linear relationship, while ageage phenotypic correlations had a strong linear relationship with natural logarithm of age ratio. Optimum selection age for core density was estimated to be 5 years when calculations were based on both genetic and phenotypic correlations. However, age 5 was the youngest examined in this study and optimum selection age may be younger than 5. Generally, the optimum selection age was robust to changes in breeding phase and assumptions concerning age-related variation in heritability estimates. Early selection for core density would result in a correlated increase in earlywood density but little progress in latewood density or latewood proportion at maturity.

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Pantelic, V., D. Niksic, D. Ostojic-Andric, Z. Novakovic, D. Ruzic-Muslic, N. Maksimovic, and M. Lazarevic. "Phenotypic and genetic correlations of milk and type traits of Holstein-Friesian bull dams." Biotehnologija u stocarstvu 28, no. 1 (2012): 1–10. http://dx.doi.org/10.2298/bah1201001p.

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The study of the production capacities of cattleaimed at increase of the capacity of cattle to produce milk, milk fat and calves, greatly depends on pehotypic and genetic variability, heritability and correlation between preferable traits, as well as level of production in the population. Objective of the study was to calculate the variability, phenotypic and genetic correlation of milk and type traits by applying the method of linear scoring of cows in the nucleus herd of Holstein-Friesian bull dams and also to determine their significance in cattle selection. For all studied traits, main variation-statistical parameters were calculated by applying method of least squares: arithmetic mean, standard deviation, variation coefficient, standard error and variation interval. Negative phenotypic correlations between production of milk and type traits ranged from -0.12 (rear leg set, side view) to -0.01 (rump height and body depth) and positive from 0.03 (rear teat placement) to 0.23 (suspensory ligament). Phenotypic correlations between milk fat percentage and type traits varied in the range from -0.08 (fore teat placement) to 0.14 (rump height). Negative genetic correlations between milk production and type traits ranged from -0.11 (rear udder height) to -0.01 (rump width and dairy form), and positive from 0.03 (rear legs set, rear view) to 0.23 (suspensory ligament). Genetic correlations between the percentage of milk fat and type traits ranged from -0.15 (pelvic position) to 0.18 (rump height). Information about phenotypic and genetic correlations between milk and type traits can be of multiple significance in cow selection since it offers possibility to select heads of cattle for multiple traits at the same time.

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Opoku, Prince P., Bimol Roy, Graham Plastow, huaigang Lei, Chunyan Zhang, Heather L. Bruce, and Le Luo Guan. "PSVIII-32 Estimates of genetic parameters for sub-primal and meat quality traits in Canadian commercial crossbred swine populations." Journal of Animal Science 97, Supplement_3 (December 2019): 270–71. http://dx.doi.org/10.1093/jas/skz258.549.

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Abstract The hypothesis that genetic relationships exist between loin muscle collagen characteristics and sub-primal and meat quality traits was tested. Data from 500 pigs from crosses between Duroc sires and hybrid Large White ✕ Landrace sows with pedigree back to about eight generations were used. Significant fixed effects (slaughter group and company) and a random additive effect were fitted in bivariate animal models to estimate phenotypic and genetic correlations using ASReml 4.1. Moderate heritabilities were obtained for sub-primal traits ranging from 0.21 for bone weight to 0.44 for loin muscle weight with a low estimate of 0.10 being obtained for loin weight. Meat quality traits were low to moderately heritable with the highest estimate being found for intramuscular fat (0.42). The heritability estimates for percentages of heat soluble and insoluble collagen were 0.12 and 0.15, respectively, while 0.33 was found for total collagen. Moderate to relatively high heritabilities imply the possibility of improving these traits through selective breeding. In general, moderate to high phenotypic and genetic correlations were obtained for sub-primal traits, whilst meat quality traits had moderate phenotypic and moderate to high genetic correlations. Strong negative genetic correlations between moisture traits and fat traits and a further negative correlation between fat and muscling traits were estimated confirming that selecting for improved muscling over time can negatively affect fat traits and indirectly decrease meat eating quality. The strong genetic correlation between pH and L* (-0.95) suggested possible pleiotropic gene effects on these traits. Warner-Braztler shear force (WBSF) had moderate genetic correlations with insoluble collagen (0.42) and soluble collagen (-0.38) suggesting a potential relationship between some of the genes impacting these traits. Genetic correlations between WBSF and collagen characteristics indicate that despite the relative youthfulness of pigs at slaughter, genetic selection for collagen solubility may decrease pork toughness.

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Odubute, I. K., and J. O. Akinokun. "ESTIMATES OF PHENOTYPIC AND GENETIC CORRELATIONS IN WEST AFRICAN DWARF GOATS." Nigerian Journal of Animal Production 21 (January 3, 2021): 47–50. http://dx.doi.org/10.51791/njap.v21i1.1096.

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Records on 848 West African dwarf goat kids and 220 kiddings over a period of eight year's (1982-1989) were analyzed. The records were used to provide estimates of phenotypic and venetic correlations among parity, kidding interval, litter size at birth and body weight at various ages. Plenotypic correlation coefficients of +0.33 (P<0.01) and -0,17 (P<0.01) were obtained when parity was correlated with litter size at birth and kidding interval respectively. Phenotypic correlations among body weights were generally positive and significant (P<0.01). Parity was positively correlated (P<0.01) with body weight at the various ages except at 1 year (P>0.05). Litter size was, however, negatively correlated (P<0.01) with body weight at the various ages except at 1 year (P<0.05). The genetic correlations among body weights at variuus ages were positive and significant (P<0.01). Selection for body weight at in earlier age especially at 3 months is likely to result in improvement of yearling body weight.

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Sreckov, Zorana, Jan Bocanski, and Mile Ivanovic. "Genetic and phenotypic correlations between oil content and morphological traits in high oil maize population NSU1." Genetika 39, no. 2 (2007): 103–12. http://dx.doi.org/10.2298/gensr0702103s.

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In this paper we are studied correlations between grain yield and oil content, on one side, and morphological traits of plant and ear, on the other side, in two testcross maize populations. In testcross combination NSU1 ? 568/II NS, oil content had positive genetic correlation with all studied traits. At the second studied population, NSU1 ? B73, oil content had positive correlation only with ear height and ear length, while correlation between oil content and plant height and kernel row number were negative. Between other studied traits, at 568/II testcrosses, the strongest relationship was found between plant and ear height, and at B73 testcrosses between plant height and ear length. In NSU1 ? 568/II NS, oil content had positive phenotypic correlations with all traits, except, with a kernel row number. In the second studied population, phenotypic correlations between oil content and all traits (except ear length) were negative. The highest value of phenotypic correlation between another studied traits, in NSU1 ? 568/II NS testcross combination, was found between plant and ear height, and in NSU1 ? B73, between plant height and kernel row number. .

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Lopez, Bryan Irvine, Kier Gumangan Santiago, Kangseok Seo, Taejoon Jeong, Jong-Eun Park, Han-Ha Chai, Woncheoul Park, and Dajeong Lim. "Genetic Parameters of Birth Weight and Weaning Weight and Their Relationship with Gestation Length and Age at First Calving in Hanwoo (Bos taurus coreanae)." Animals 10, no. 6 (June 23, 2020): 1083. http://dx.doi.org/10.3390/ani10061083.

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Hanwoo is one of the most economically important animal species in Korea due to its significant contribution to nutrition. However, the current selection index only focuses to improve carcass traits of Hanwoo. Thus, this study aimed to estimate the genetic parameters of birth weight (BW) and weaning weight (WW) and their genetic and phenotypic relationship to the age at first calving (AFC) and gestation length (GL) of Hanwoo. The genetic parameters for birth weight (BW) and weaning weight (WW) were estimated using the data obtained from 52,173 and 35,800 Hanwoo calves born from February 1998 to March 2017, respectively. Further, these data were used to determine their genetic and phenotypic correlation to age at first calving (AFC) and gestation length (GL). The heritability estimates of BW and WW and correlation coefficients were obtained using the average information restricted maximum likelihood (AIREML) procedure, fit in single and two-trait linear animal models. The estimated direct heritability for BW and WW was moderate (0.22 ± 0.02) and high (0.51 ± 0.03), respectively, while the maternal heritability for both traits was 0.12 ± 0.01 and 0.17 ± 0.01, respectively. The genetic correlation of BW and reproductive traits (AFC and GL) showed a moderate and high positive correlation coefficient of 0.33 ± 0.06 and 0.53 ± 0.02, respectively, while close to zero and low positive phenotypic correlations of 0.06 ± 0.01 and 0.21 ± 0.06 were also observed between the correlated traits, respectively. For the correlation analysis between WW and AFC, both the genetic and phenotypic correlation showed close to zero values of 0.04 ± 0.06 and −0.01 ± 0.01, respectively. Meanwhile, the genetic and phenotypic correlation between WW and GL showed low and negative correlations of −0.09 ± 0.06 and −0.09 ± 0.01, respectively. These obtained estimated variances for BW and WW and their corresponding genetic and phenotypic correlation to AFC and GL can be used as information for genetic improvement and subsequent economic improvement of Hanwoo farming.

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Buzatto, Bruno A., Mathieu Buoro, Wade N. Hazel, and Joseph L. Tomkins. "Investigating the genetic architecture of conditional strategies using the environmental threshold model." Proceedings of the Royal Society B: Biological Sciences 282, no. 1821 (December 22, 2015): 20152075. http://dx.doi.org/10.1098/rspb.2015.2075.

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The threshold expression of dichotomous phenotypes that are environmentally cued or induced comprise the vast majority of phenotypic dimorphisms in colour, morphology, behaviour and life history. Modelled as conditional strategies under the framework of evolutionary game theory, the quantitative genetic basis of these traits is a challenge to estimate. The challenge exists firstly because the phenotypic expression of the trait is dichotomous and secondly because the apparent environmental cue is separate from the biological signal pathway that induces the switch between phenotypes. It is the cryptic variation underlying the translation of cue to phenotype that we address here. With a ‘half-sib common environment’ and a ‘family-level split environment’ experiment, we examine the environmental and genetic influences that underlie male dimorphism in the earwig Forficula auricularia . From the conceptual framework of the latent environmental threshold (LET) model, we use pedigree information to dissect the genetic architecture of the threshold expression of forceps length. We investigate for the first time the strength of the correlation between observable and cryptic ‘proximate’ cues. Furthermore, in support of the environmental threshold model, we found no evidence for a genetic correlation between cue and the threshold between phenotypes. Our results show strong correlations between observable and proximate cues and less genetic variation for thresholds than previous studies have suggested. We discuss the importance of generating better estimates of the genetic variation for thresholds when investigating the genetic architecture and heritability of threshold traits. By investigating genetic architecture by means of the LET model, our study supports several key evolutionary ideas related to conditional strategies and improves our understanding of environmentally cued decisions.

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LYNCH, MICHAEL. "Estimating genetic correlations in natural populations." Genetical Research 74, no. 3 (December 1999): 255–64. http://dx.doi.org/10.1017/s0016672399004243.

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Information on the genetic correlation between traits provides fundamental insight into the constraints on the evolutionary process. Estimates of such correlations are conventionally obtained by raising individuals of known relatedness in artificial environments. However, many species are not readily amenable to controlled breeding programmes, and considerable uncertainty exists over the extent to which estimates derived under benign laboratory conditions reflect the properties of populations in natural settings. Here, non-invasive methods that allow the estimation of genetic correlations from phenotypic measurements derived from individuals of unknown relatedness are introduced. Like the conventional approach, these methods demand large sample sizes in order to yield reasonably precise estimates, and special precautions need to be taken to eliminate bias from shared environmental effects. Provided the sample consists of at least 20% or so relatives, informative estimates of the genetic correlation are obtainable with sample sizes of several hundred individuals, particularly if supplemental information on relatedness is available from polymorphic molecular markers.

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Sabri, Hani M., Henry R. Wilson, Robert H. Harms, and Charles J. Wilcox. "Genetic parameters for egg and related characteristics of white Leghorn hens in a subtropical environment." Genetics and Molecular Biology 22, no. 2 (June 1999): 183–86. http://dx.doi.org/10.1590/s1415-47571999000200008.

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Estimates of heritability and phenotypic and genetic correlations between egg number, weight, specific gravity, mass, and estimated shell weight were obtained, along with phenotypic and genetic correlations of specific gravity and weight with body weight, weight change, metabolizable energy intake, residual feed consumption, and weight and age at sexual maturity. Data were from 350 White Leghorn hens by 50 sires and 175 dams. Heritabilities of the egg traits ranged from 0.20 to 0.55, increasing with age of bird from 26 to 54 weeks of age. Their standard errors ranged from 0.07 (all data) to 0.17 (26 to 29 weeks). Phenotypic correlations ranged from 0.80 to -0.13, and genetic correlations from 0.91 to -0.27, depending on egg trait. The highest phenotypic and genetic correlations were between egg number and mass. Genetic correlations for specific gravity and estimated shell weight were, with body weight, -0.02 and 0.56; weight change, 0.29 and 0.44; daily metabolizable energy intake, -0.10 and 0.33; residual consumption, -0.16 and 0.11; age at sexual maturity, -0.61 and -0.46, and weight at sexual maturity, 0.02 and 0.63. Results should contribute to the design of efficient selection programs for economically important traits in hens.

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Khanal, Piush, Christian Maltecca, Clint Schwab, Kent Gray, and Francesco Tiezzi. "Genetic parameters of meat quality, carcass composition, and growth traits in commercial swine." Journal of Animal Science 97, no. 9 (July 28, 2019): 3669–83. http://dx.doi.org/10.1093/jas/skz247.

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Abstract Swine industry breeding goals are mostly directed towards meat quality and carcass traits due to their high economic value. Yet, studies on meat quality and carcass traits including both phenotypic and genotypic information remain limited, particularly in commercial crossbred swine. The objectives of this study were to estimate the heritabilities for different carcass composition traits and meat quality traits and to estimate the genetic and phenotypic correlations between meat quality, carcass composition, and growth traits in 2 large commercial swine populations: The Maschhoffs LLC (TML) and Smithfield Premium Genetics (SPG), using genotypes and phenotypes data. The TML data set consists of 1,254 crossbred pigs genotyped with 60K SNP chip and phenotyped for meat quality, carcass composition, and growth traits. The SPG population included over 35,000 crossbred pigs phenotyped for meat quality, carcass composition, and growth traits. For TML data sets, the model included fixed effects of dam line, contemporary group (CG), gender, as well as random additive genetic effect and pen nested within CG. For the SPG data set, fixed effects included parity, gender, and CG, as well as random additive genetic effect and harvest group. Analyses were conducted using BLUPF90 suite of programs. Univariate and bivariate analyses were implemented to estimate heritabilities and correlations among traits. Primal yield traits were uniquely created in this study. Heritabilities [high posterior density interval] of meat quality traits ranged from 0.08 [0.03, 0.16] for pH and 0.08 [0.03, 0.1] for Minolta b* to 0.27 [0.22, 0.32] for marbling score, except intramuscular fat with the highest estimate of 0.52 [0.40, 0.62]. Heritabilities of primal yield traits were higher than that of primal weight traits and ranged from 0.17 [0.13, 0.25] for butt yield to 0.45 [0.36, 0.55] for ham yield. The genetic correlations of meat quality and carcass composition traits with growth traits ranged from moderate to high in both directions. High genetic correlations were observed for male and female for all traits except pH. The genetic parameter estimates of this study indicate that a multitrait approach should be considered for selection programs aimed at meat quality and carcass composition in commercial swine populations.

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Adams, Paul C., and Subrata Chakrabarti. "Genotypic/phenotypic correlations in genetic hemochromatosis: Evolution of diagnostic criteria." Gastroenterology 114, no. 2 (February 1998): 319–23. http://dx.doi.org/10.1016/s0016-5085(98)70483-4.

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Warrier, Varun, Mariana Vieira, and Sara E. Mole. "Genetic basis and phenotypic correlations of the neuronal ceroid lipofusinoses." Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1832, no. 11 (November 2013): 1827–30. http://dx.doi.org/10.1016/j.bbadis.2013.03.017.

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Araújo, Marcelo Renato Alves de, and Bruce Coulman. "Genetic variation and correlation of agronomic traits in meadow bromegrass (Bromus riparius Rehm) clones." Ciência Rural 34, no. 2 (April 2004): 505–10. http://dx.doi.org/10.1590/s0103-84782004000200026.

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Meadow bromegrass (Bromus riparius Rehm.) is a recently introduced pasture grass in western Canada. Its leafy production and rapid regrowth have made it a major grass species for pasturing beef animals in this region. As relatively little breeding work has been done on this species, there is little information on its breeding behaviour. The main objective of this study was to estimate total genetic variability, broad-sense heritability, phenotypic and genetic correlations. Forty-four meadow bromegrass clones were evaluated for agronomic characters. Genetic variation for dry matter yield, seed yield, fertility index, harvest index, plant height, plant spread, crude protein, neutral detergent fiber and acid detergent fiber, was significant. Broad-sense heritability estimates exceeded 50% for all characters. Heritability estimates were at least 3.5 times greater than their standard errors. Phenotypic and genetic correlation between all possible characters were measured. There was general agreement in both sign and magnitude between genetic and phenotypic correlations. Correlations between the different characters demonstrated that it is possible to simultaneously improve seed and forage yield. Based on the results, it appears that the development of higher yielding cultivars with higher crude protein, and lower acid and neutral detergent fibers concentration should be possible.

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Cohen, M. Michael. "Craniosynostoses: Phenotypic/molecular correlations." American Journal of Medical Genetics 56, no. 3 (1995): 334–39. http://dx.doi.org/10.1002/ajmg.1320560327.

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Onley, Michael, Livia Veselka, Julie Aitken Schermer, and Philip A. Vernon. "Survival of the Scheming: A Genetically Informed Link Between the Dark Triad and Mental Toughness." Twin Research and Human Genetics 16, no. 6 (September 27, 2013): 1087–95. http://dx.doi.org/10.1017/thg.2013.66.

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The present study is the first behavioral genetic investigation of the Dark Triad traits of personality, consisting of Machiavellianism, narcissism, and psychopathy, and the variable of mental toughness, reflecting individual differences in the ability to cope when under pressure. The purpose of this investigation was to explore a potential explanation for the success of individuals exhibiting the Dark Triad traits in workplace and social settings. Participants were adult twins who completed the MACH-IV, the Narcissistic Personality Inventory, and the Self-Report Psychopathy Scale assessing Machiavellianism, narcissism, and psychopathy, respectively, as well as the MT48, measuring mental toughness. Correlational analyses of the data revealed significant positive phenotypic associations between mental toughness and narcissism. Psychopathy and Machiavellianism, however, both showed some significant negative phenotypic correlations with mental toughness. Bivariate behavioral genetic analyses of the data were conducted to assess the extent to which these significant phenotypic correlations were attributable to common genetic and/or common environmental factors. Results indicate that correlations between narcissism and mental toughness were attributable primarily to common non-shared environmental factors, correlations between Machiavellianism and mental toughness were influenced by both common genetic and common non-shared environmental factors, and the correlations between psychopathy and mental toughness were attributable entirely to correlated genetic factors. Implications of these findings in the context of etiology and organizational adaptation are discussed.

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Yakovlev, A. N., N. V. Pashkevich, and V. I. Vitchinkina. "Genetic risks of addictive disorders in adolescents: phenotypic effects." V.M. BEKHTEREV REVIEW OF PSYCHIATRY AND MEDICAL PSYCHOLOGY, no. 4-1 (December 9, 2019): 73–74. http://dx.doi.org/10.31363/2313-7053-2019-4-1-73-7.

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In several unrelated small samples examined correlation between genetic risk of chemical dependence, calculated on the basis of the contribution of geomarkers dopamine system, and phenotype of adolescents 14-17 years of age, not suffering from addiction. When genetic risk increases, the tendency to behavioural disorders increases, the tendency to abandon positive forms of self-assertion increases, the intensity of euphoria increases at the first drug samples, and the ability to predict the consequences of drug use decreases. The obtained correlations may be important for understanding the mechanism of dependence formation in adolescents with high genetic risk and development of individual prevention programs. However, these observations need to be confirmed in more representative studies.

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Wu, Yuchang, Xiaoyuan Zhong, Yunong Lin, Zijie Zhao, Jiawen Chen, Boyan Zheng, James J. Li, Jason M. Fletcher, and Qiongshi Lu. "Estimating genetic nurture with summary statistics of multigenerational genome-wide association studies." Proceedings of the National Academy of Sciences 118, no. 25 (June 15, 2021): e2023184118. http://dx.doi.org/10.1073/pnas.2023184118.

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Marginal effect estimates in genome-wide association studies (GWAS) are mixtures of direct and indirect genetic effects. Existing methods to dissect these effects require family-based, individual-level genetic, and phenotypic data with large samples, which is difficult to obtain in practice. Here, we propose a statistical framework to estimate direct and indirect genetic effects using summary statistics from GWAS conducted on own and offspring phenotypes. Applied to birth weight, our method showed nearly identical results with those obtained using individual-level data. We also decomposed direct and indirect genetic effects of educational attainment (EA), which showed distinct patterns of genetic correlations with 45 complex traits. The known genetic correlations between EA and higher height, lower body mass index, less-active smoking behavior, and better health outcomes were mostly explained by the indirect genetic component of EA. In contrast, the consistently identified genetic correlation of autism spectrum disorder (ASD) with higher EA resides in the direct genetic component. A polygenic transmission disequilibrium test showed a significant overtransmission of the direct component of EA from healthy parents to ASD probands. Taken together, we demonstrate that traditional GWAS approaches, in conjunction with offspring phenotypic data collection in existing cohorts, could greatly benefit studies on genetic nurture and shed important light on the interpretation of genetic associations for human complex traits.

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Journal articles on the topic 'Genetic and Phenotypic Correlations'

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