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Strong Genetic Correlations (strong + genetic_correlation)
Selected AbstractsApplication of REML procedure to estimate the genetic parameters of weekly liveweights in one-to-one sire and dam pedigree recorded Japanese quailJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 1 2003M. Saatci Summary Residual maximum likelihood procedure was applied to analyse data from a one-to-one pedigreed Japanese quail population, using an animal model to estimate the genetic parameters of weekly liveweights. Records of 1108 animals from 113 sires and 152 dams were analysed. An individual animal model was used. The heritabilities of weights for hatching (HW) with their standard errors (SE), week 1 (W1), week 2 (W2), week 3 (W3), week 4 (W4), week 5 (W5) and week 6 (W6) were 0.51 ± 0.05, 0.32 ± 0.06, 0.20 ± 0.05, 0.21 ± 0.06, 0.20 ± 0.05, 0.15 ± 0.04 and 0.14 ± 0.04, respectively. The strongest genetic correlations were found between W1 and W3 (0.98 ± 0.11). Generally, genetic correlations were higher than the phenotypic correlations. The highest phenotypic correlation (0.85) was between the W4 and W5 weights. Strong genetic correlations among the weekly weights suggest that selection for W5 or W6 weight may be based on weights recorded earlier. Zusammenfassung Die Anwendung der REML-Methode zur Schätzung von genetischen Parametern für Wochengewichte bei japanischen Wachteln mit Abstammungsinformationen Die REML-Methode zur Varianzkomponentenschätzung mittels eines Tiermodells wurde für eine Population von japanischen Wachteln mit Abstammungsinformationen für Wochengewichte angewandt. Daten von 1108 Tieren von 113 Vätern und 152 Müttern wurden mit einem Tiermodell analysiert. Folgende Heritabilitäten wurden geschätzt: 0,51 ± 0,05 für Schlupfgewicht (HW), 0,32 ± 0,06 für Gewicht 1. Woche (W1), 0,20 ± 0,05 für Gewicht 2. Woche (W2), 0,21 ± 0,06 für Gewicht 3. Woche (W3), 0,20 ± 0,05 für Gewicht 4. Woche (W4), 0,15 ± 0,04 für Gewicht 5. Woche (W5) und 0,14 ± 0,04 für Gewicht 6. Woche (W6). Die höchste genetischen Korrelation wurde zwischen W1 und W3 gefunden (0,98 ± 0,11). Generell waren die genetischen Korrelationen höher als die phänotypischen. Die höchste phänotypische Korrelation (0,85) wurde zwischen den Gewichten in der 4. und 5. Woche beobachtet. Die hohen genetischen Korrelationen führen zu der Konsequenz, dass auf die Gewichte der 5. und 6. Woche selektiert werden kann unter Nutzung der früheren Wochengewichte. [source] Heritable variation and genetic correlation of quantitative traits within and between ecotypes of Avena barbataJOURNAL OF EVOLUTIONARY BIOLOGY, Issue 3 2008K. M. GARDNER Abstract We examined heritable variation for quantitative traits within and between naturally occurring mesic and xeric ecotypes of the slender wild oat (Avena barbata), and in 188 recombinant inbred lines derived from a cross between the ecotypes. We measured a suite of seedling and adult traits in the greenhouse, as well as performance-related traits in field sites native to the two ecotypes. Although the ecotypes were genetically diverged for most traits, few traits showed significant heritable variation within either ecotype. In contrast, considerable heritable variation was released in the recombinant progeny of the cross, and transgressive segregation was apparent in all traits. Heritabilities were substantially greater in the greenhouse than in the field, and this was associated with an increase in environmental variance in the field, rather than a decrease in genetic variance. Strong genetic correlations were evident among the recombinants, such that 22 measured traits could be well represented by only seven underlying factors, which accounted for 80% of the total variation. The primary axis of variation in the greenhouse described a trade-off between vegetative and reproductive allocation, mediated by the date of first flowering, and fitness was strongly correlated with this trade-off. Other factors in the greenhouse described variation in size and in seedling traits. Lack of correlation among these factors represents the release of multivariate trait variation through recombination. In the field, a separate axis of variation in overall performance was found for each year/site combination. Performance was significantly correlated across field environments, but not significantly correlated between greenhouse and field. [source] CONSTANCY OF THE G MATRIX IN ECOLOGICAL TIMEEVOLUTION, Issue 6 2004Mats BjÖrklund Abstract The constancy of the genetic variance-covariance matrix (G matrix) across environments and populations has been discussed and tested empirically over the years but no consensus has so far been reached. In this paper, I present a model in which morphological traits develop hierarchically, and individuals differ in their resource allocation and acquisition patterns. If the variance in resource acquisition is many times larger than the variance in resource allocation then strong genetic correlations are expected, and with almost isometric relations among traits. As the variation in resource acquisition decreases below a certain threshold, the correlations decrease overall and the relations among traits become a function of the allocation patterns, and in particular reflecting the basal division of allocation. A strong bottleneck can break a pattern of strong genetic correlation, but this effect diminishes rapidly with increasing bottleneck size. This model helps to understand why some populations change their genetic correlations in different environments, whereas others do not, since the key factor is the relation between the variances in resource acquisition and allocation. If a change in environment does not lead to a change in this ratio, no change can be expected, whereas if the ratio is changed substantially then major changes can be expected. This model can also help to understand the constancy of morphological patterns within larger taxa as a function of constancy in resource acquisition patterns over time and environments. When this pattern breaks, for example on islands, larger changes can be expected. [source] Sociability and Positive Emotionality: Genetic and Environmental Contributions to the Covariation Between Different Facets of ExtraversionJOURNAL OF PERSONALITY, Issue 3 2003Michael Eid The relation between sociability and positive affect is one of the most often replicated results of research on personality and subjective well-being. It is shown how behavior genetics can contribute to our understanding of the covariance between sociability and positive emotionality. The results of a multimethod behavior-genetic study with 158 monozygotic and 120 dizygotic twins are reported. In this study, sociability and two components of positive emotionality (positive affect, energy) were assessed by self-report and other report. Additionally, positive state affect was assessed in five situations and aggregated across situations. The results showed that there are strong genetic correlations between all variables. Furthermore, there are substantive correlations between the nonshared environmental components of the different variables. Shared environmental influences, however, seemed to be unimportant for explaining the correlations between sociability and the different components of positive emotionality. The results are discussed with respect to their implications for future research on sociability and positive emotionality. [source] | ||||||||||