COMPARISON OF PREDICTED AND SIMULATED RESPONSES TO S1 SELECTION IN A DIPLOID, CROSS-FERTILIZED SPECIES

1981 ◽  
Vol 61 (1) ◽  
pp. 9-15 ◽  
Author(s):  
T. M. CHOO ◽  
L. W. KANNENBERG
Keyword(s):  
Coefficient Of Variation ◽  
Variance Component ◽  
Genetic Variance ◽  
Recurrent Selection ◽  
Genetic Models ◽  
Variance Component Analysis ◽  
Narrow Sense Heritability ◽  
Complete Dominance ◽  
Per Se ◽  
Good Agreement

Computer simulation was used to test the accuracy of mathematical formulae for predicting mean response and variance of response to S1 per se recurrent selection under both additive and complete dominance genetic models. S1 selection was simulated at two levels of selection intensity (5 and 25%) and two levels of narrow sense heritability (0.2 and 0.6) for 15 cycles. In each cycle, 400 S1 families were evaluated in simulated trials consisting of one replication of 10-plant plots at each of four locations. The character under selection was controlled by 40 independently assorted loci. For both genetic models, variance component analysis provided good estimates of genetic variance and the predicted gains were in good agreement with the simulated gains. The simulated coefficient of variation of response was small and was very close to the predicted coefficient of variation in each of the four selection regimes under both models.

scholarly journals Genetic Variance Component and Heritability Estimates of Freedom from Weevil Injury to Sweetpotato

1994 ◽  
Vol 119 (3) ◽  
pp. 620-623 ◽  
Author(s):  
P.G. Thompson ◽  
John C. Schneider ◽  
Boyett Graves
Keyword(s):  
Variance Component ◽  
Genetic Variance ◽  
Genetic Correlations ◽  
Component Analysis ◽  
Variance Component Analysis ◽  
Breeding Cycle ◽  
Individual Plant ◽  
Root Number ◽  
Narrow Sense Heritability ◽  
Heritability Estimates

Narrow-sense heritability for component traits of freedom from weevil injury and yield of sweetpotato were estimated by parent-offspring regression and variance component analysis. Heritability estimates by variance component analysis based on half-sib families for percent and number of uninjured roots were 0.25 and 0.83, respectively. Individual plant heritability estimates for uninjured root percent and number were 0.03 and 0.13, respectively. Heritability estimates by parent-offspring regression for uninjured root percent and number were 0.35 and 0.52, respectively. Genetic variance was mostly additive for all traits except stem diameter. Genetic correlations between total root number, uninjured root number, and percent uninjured roots ranged from 0.66 to 0.87, indicating that selection for uninjured root number should most effectively increase uninjured root number and percent, as well as total root numbers. Predicted gains in uninjured root percent and number were 8.8% and 0.87 in the progeny derived from intermating the highest four out of 19 families for uninjured root number. The 0.87 gain in uninjured root number equals a 24% increase in one breeding cycle.

scholarly journals The Genetic Architecture of Quantitative Traits Cannot Be Inferred From Variance Component Analysis

2016 ◽  
Author(s):  
Wen Huang ◽  
Trudy F.C. Mackay
Keyword(s):  
Genetic Variation ◽  
Variance Components ◽  
Variance Component ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Genetic Variance ◽  
Component Analysis ◽  
Genetic Models ◽  
Variance Component Analysis ◽  
Components Of Variance

AbstractClassical quantitative genetic analyses estimate additive and non-additive genetic and environmental components of variance from phenotypes of related individuals. The genetic variance components are defined in terms of genotypic values reflecting underlying genetic architecture (additive, dominance and epistatic genotypic effects) and allele frequencies. However, the dependency of the definition of genetic variance components on the underlying genetic models is not often appreciated. Here, we show how the partitioning of additive and non-additive genetic variation is affected by the genetic models and parameterization of allelic effects. We show that arbitrarily defined variance components often capture a substantial fraction of total genetic variation regardless of the underlying genetic architecture in simulated and real data. Therefore, variance component analysis cannot be used to infer genetic architecture of quantitative traits. The genetic basis of quantitative trait variation in a natural population can only be defined empirically using high resolution mapping methods followed by detailed characterization of QTL effects.

scholarly journals Variance Component Analysis of Parthenocarpic Character in a Processing Cucumber (Cucumis sativus L.) population

HortScience ◽  
2004 ◽  
Vol 39 (4) ◽  
pp. 881A-881
Author(s):  
Zhanyong Sun* ◽  
Richard L. Lower ◽  
Jack E. Staub
Keyword(s):  
Cucumis Sativus ◽  
Variance Component ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Component Analysis ◽  
Variance Component Analysis ◽  
Individual Plant ◽  
Normal Leaf ◽  
Dominance Genetic Variance ◽  
Plant Basis

The incorporation of genes for parthenocarpy (production of fruit without fertilization) has potential for increasing yield in pickling cucumber (Cucumis sativus L.). The inheritance of parthenocarpy in cucumber is not well understood, and thus a genetic analysis was performed on F3 cross-progeny resulting from a mating between the processing cucumber inbred line 2A (P1, gynoecious, parthenocarpic, indeterminate, normal leaf) and Gy8 (P2, gynoecious, non-parthenocarpic, indeterminate, normal leaf). A variance component analysis was performed to fruit yield data collected at two locations (designated E-block and G-block) at Hancock, WI in 2000. The relative importance of additive genetic variance compared to dominance genetic variance changed across environments. The additive genetic variance was 0.5 and 4.3 times of dominance genetic variance in E-block and G-block, respectively. The estimated environmental variance accounted for ≈90% of the total phenotypic variance on an individual plant basis in both locations. Narrow-sense heritability estimated on an individual plant basis ranged from 0.04 (E-block) to 0.12 (G-block). Broad-sense heritability estimated on an individual plant basis ranged from 0.12 (E-block) to 0.15 (G-block). The minimum number of effective factors controlling parthenocarpy was estimated to range between 5 (G-block) to 13 (E-block). These results suggest that the response to direct selection of individual plants for improving parthenocarpy character will likely be slow and difficult. Experiment procedures that minimize the effect of environment on the expression of parthenocarpy will likely maximize the likelihood of gain from selection.

Breeding and selection for high early season sugar content in a sugarcane (Saccharum spp. hybrids) improvement program

1994 ◽  
Vol 45 (7) ◽  
pp. 1569 ◽  
Author(s):  
MC Cox ◽  
DM Hogarth ◽  
PB Hansen
Keyword(s):  
Genetic Variance ◽  
Recurrent Selection ◽  
Sugar Content ◽  
Additive Genetic Variance ◽  
Breeding Population ◽  
Cane Sugar ◽  
Improvement Program ◽  
Narrow Sense Heritability ◽  
Saccharum Spp ◽  
Early Season

A recurrent selection program for high early season commercial cane sugar (CCS) in sugarcane (Saccharum spp. hybrids) commenced in 1988. About 20 families (first clonal stage) and their parents are grown in two regions each year. Elite clones with high early CCS are selected and these are recycled into the breeding population with a short generation interval. Estimates of narrow-sense heritability from midparent-offspring regressions were moderate to high (0.6 or greater). Thus breeding for this trait using a large database of information available on early CCS characteristics of parental clones should be effective. Additive genetic variance (=2A) was more important than non-additive genetic variance.

scholarly journals Selection under assortative mating in mice

1968 ◽  
Vol 11 (2) ◽  
pp. 171-178 ◽  
Author(s):  
T. M. Sutherland ◽  
Patricia E. Biondini ◽  
L. H. Haverland
Keyword(s):  
Body Weight ◽  
Experimental Design ◽  
Environmental Effects ◽  
Variance Component ◽  
Mating Systems ◽  
Genetic Variance ◽  
The Other ◽  
Variance Component Analysis ◽  
The Mean ◽  
Selection Differentials

1. Approximately 25000 mice have been produced over twelve generations of selection in nine lines. The experimental design involved a 3 × 3 factorial arrangement of direction of selection with mating system. The primary character measured was 6-week body weight.2. Consistently high phenotypic correlations between mates have been achieved, positive in the assortative lines, negative in the disassortative lines. Correlations were low and inconsistent in direction in the random-bred lines. These correlations have had very little, if any, effect in redistributing the genetic variance as estimated from the variance component analysis; the expected higher variances in the assortative lines and expected lower variances in the disassortative lines have not appeared, thus leaving heritability unaffected.3. Selection differentials likewise show no consistent advantage for the assortative lines, so that the progress from selection has been virtually identical in all three mating systems in each direction.4. Assortment of mates, either positively or negatively, for characters of even moderate heritability appears to have little influence on the outcome of selection. On the other hand, selection has been singularly effective in modifying the mean 6-week weight, with progress markedly greater in the downward direction; indeed it appears that the lower limit, may already have been approximately attained.5. Environmental effects operating in the various generations have affected all lines in remarkably consistent fashion.

scholarly journals Genetic variance and covariance components related to intra- and interpopulation recurrent selection in maize (Zea mays L.)

1998 ◽  
Vol 21 (4) ◽  
pp. 537-544 ◽  
Author(s):  
Carlos Alberto Arrabal Arias ◽  
Cláudio Lopes de Souza Júnior
Keyword(s):  
Zea Mays ◽  
Genetic Variance ◽  
Recurrent Selection ◽  
Zea Mays L ◽  
Inbred Lines ◽  
Additive Effects ◽  
Covariance Components ◽  
Per Se ◽  
Variance And Covariance Components ◽  
Variance Estimates

New genetic variance and covariance components related to intra- and interpopulational recurrent selection methods have been theoretically developed by Souza Jr. (Rev. Bras. Genet. 16: 91-105, 1993) to explain the failure of these methods to concomitantly develop hybrid and per se populations. Intra- and interpopulation half-sib progenies of 100 genotypes were sampled from maize (Zea mays L.) populations BR-106 and BR-105 to estimate variance and covariance components and to compare the expected responses to reciprocal (RRS), intrapopulational (HSS), and modified (MRS) recurrent selection in interpopulation hybrid, populations per se, and to determine heterosis. Four sets of 100 progenies, two intra- and two interpopulational, were evaluated in partially balanced 10 x 10 lattices arranged in split-blocks with two replications in two years (1991/92 and 1992/93) and two locations in Piracicaba, SP. Data for ear weight, plant and ear height, and ear by plant height ratio were recorded. Populations and interpopulation crosses were high yielding and showed high breeding potential for production of hybrids from inbred lines. Mid parent and the highest parent heterosis were relatively high, but lower than values reported for these populations under other environmental conditions. Additive variance estimates of populations per se and interpopulation crosses confirmed the high potential of these materials. The magnitude of the variance estimates for the deviations from intra- and interpopulation additive effects (<img src="http:/img/fbpe/gmb/v21n4/1918f1.jpg" alt="1918f1.jpg (1262 bytes)" align="middle"> for BR-106 and <img src="http:/img/fbpe/gmb/v21n4/1918f3.jpg" alt="1918f3.jpg (1259 bytes)" align="middle">for BR-105) and covariance between additive effects with these deviations (<img src="http:/img/fbpe/gmb/v21n4/1918f2.jpg" alt="1918f2.jpg (2022 bytes)" align="middle"> for BR-106 and <img src="http:/img/fbpe/gmb/v21n4/1918f4.jpg" alt="1918f4.jpg (1995 bytes)" align="middle"> for BR-105) indicated that these new components can significantly influence the effectiveness of breeding methods. Genetic component estimates for BR-105 had relatively small errors, with <img src="http:/img/fbpe/gmb/v21n4/1918f4.jpg" alt="1918f4.jpg (1995 bytes)" align="middle"> negative for all traits. Estimates of <img src="http:/img/fbpe/gmb/v21n4/1918f1.jpg" alt="1918f1.jpg (1262 bytes)" align="middle">and <img src="http:/img/fbpe/gmb/v21n4/1918f2.jpg" alt="1918f2.jpg (2022 bytes)" align="middle"> had relatively larger errors for BR-106. The MRS method was more effective than the RRS and HSS methods in producing hybrids from inbred lines. The choice of a population tester for the MRS method based on population means per se may be incorrect. The additional use, when possible, of intra- and interpopulation additive genetic variances from each population would be more appropriate.

scholarly journals Genetic and environmental architecture of conscientiousness in adolescence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yusuke Takahashi ◽  
Anqing Zheng ◽  
Shinji Yamagata ◽  
Juko Ando
Keyword(s):  
Individual Differences ◽  
Effortful Control ◽  
Genetic Variance ◽  
Genetic Factors ◽  
Common Factor ◽  
Genetic Correlations ◽  
Self Control ◽  
Genetic Analyses ◽  
Environmental Correlations ◽  
Per Se

AbstractUsing a genetically informative design (about 2000 twin pairs), we investigated the phenotypic and genetic and environmental architecture of a broad construct of conscientiousness (including conscientiousness per se, effortful control, self-control, and grit). These four different measures were substantially correlated; the coefficients ranged from 0.74 (0.72–0.76) to 0.79 (0.76–0.80). Univariate genetic analyses revealed that individual differences in conscientiousness measures were moderately attributable to additive genetic factors, to an extent ranging from 62 (58–65) to 64% (61–67%); we obtained no evidence that shared environmental influences were observed. Multivariate genetic analyses showed that for the four measures used to assess conscientiousness, genetic correlations were stronger than the corresponding non-shared environmental correlations, and that a latent common factor accounted for over 84% of the genetic variance. Our findings suggest that individual differences in the four measures of conscientiousness are not distinguishable at both the phenotypic and behavioural genetic levels, and that the overlap was substantially attributable to genetic factors.

High Heritability of Glycyrrhizic Acid, Glabridin, Liquiritin and Liquiritigenin in Licorice (Glycyrrhiza Glabra L.) Populations of Iran

2021 ◽  
Author(s):  
Ghasem Eghlima ◽  
Mohsen Sanikhani ◽  
Azizollah Kheiry ◽  
Javad Hadian
Keyword(s):  
Coefficient Of Variation ◽  
Morphological Traits ◽  
Glycyrrhizic Acid ◽  
Correlation Coefficients ◽  
Glycyrrhiza Glabra ◽  
Broad Sense ◽  
Phenotypic Correlation ◽  
Broad Sense Heritability ◽  
Narrow Sense Heritability ◽  
Perennial Plant

Abstract Glycyrrhiza glabra L. is an herbaceous, perennial plant with high distribution in Iran. Genetic variability, heritability and correlation among characters in 22 populations of G. glabra L. were studied. The genetic parameters among the traits including phenotypic variances, genotypic variances, genotype by environment variances, broad-sense heritability and genotypic and phenotypic correlation coefficients were studied. Variance components analysis showed that the extent of phenotypic coefficient of variation (PCV) was fairly higher for all the examined traits compared with genotypic coefficient of variation (GCV). Glabridin (GLA) exhibited high GCV and PCV (156.07% and 156.68%, respectively). The broad sense heritability varied from 38.92–99.79% and narrow sense heritability ranged from 9.70 % to 24.94%. Heritability of GLA, glycyrrhizic acid (GLY), liquiritin (LI), liquiritigenin (LIQ), rutin (RU) and rosmarinic acid (RA) were very high, exhibiting more than 97% heritability. Therefore, these critical characteristics can efficiently be selected and inherited in breeding programs. In most traits, the genotypic correlations showed the same direction as the phenotypic correlations. The contents of GLA and LIQ showed a positive correlation with majority of morphological traits. Therefore, selecting individual plants having desired morphological traits can be correlated with high contents of bioactive compounds in the harvested root.

scholarly journals Selection strategies of segregant soybean populations for resistance to Asian rust

2009 ◽  
Vol 44 (11) ◽  
pp. 1452-1459 ◽  
Author(s):  
Aliny Simony Ribeiro ◽  
José Francisco Ferraz de Toledo ◽  
Magno Antonio Patto Ramalho
Keyword(s):  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Infected Leaf ◽  
Good Resistance ◽  
Narrow Sense Heritability ◽  
Growing Seasons ◽  
Selection Strategies ◽  
Line Selection ◽  
Soybean Resistance ◽  
Selection Of

The objective of this work was to identify the best selection strategies for the more promising parental combinations to obtain lines with good resistance to soybean Asian rust (Phakopsora pachyrhizi). Two experiments were carried out in the field during the 2006/2007 and 2007/2008 growing seasons, to determine the percentage of infected leaf area of individual plants of five parents and their segregant F2 and F3 populations. The data obtained indicates that additive genetic variance predominates in the control of soybean resistance to Asian rust, and that the year and time of assessment do not significantly influence the estimates of the genetic parameters obtained. The narrow-sense heritability (h²r) ranged from 23.12 to 55.83%, and indicates the possibility of successful selection of resistant individuals in the early generations of the breeding program. All the procedures used to select the most promising populations to generate superior inbred lines for resistance to P. pachyrhizi presented similar results and identified the BR01-18437 x BRS 232 population as the best for inbred line selection.

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