scholarly journals Environmental Variance Components of Fruit Ripening Date as Used in Both Phenotypic and Marker-assisted Selection in Japanese Pear Breeding

HortScience ◽  
2011 ◽  
Vol 46 (11) ◽  
pp. 1540-1544 ◽  
Author(s):  
Sogo Nishio ◽  
Masahiko Yamada ◽  
Yutaka Sawamura ◽  
Norio Takada ◽  
Toshihiro Saito
Keyword(s):  
Fruit Ripening ◽  
Variance Components ◽  
Genetic Variance ◽  
Japanese Pear ◽  
Pyrus Pyrifolia ◽  
Phenotypic Variance ◽  
Environmental Variance ◽  
Single Tree ◽  
Sib Families ◽  
Qtl Effects

The effectiveness of detected quantitative trait loci (QTLs) and molecular markers associated with them in tree fruit breeding is measured by the percentages of the variance associated with detected QTL effects accounting for not phenotypic variance, but genetic variance of the trait. The genetic variance can be obtained by subtracting environmental variance from the phenotypic variance. Once accurate environmental variance components are obtained for a given selection field, environmental variances under any number of replications and measurement repetitions can be estimated. We estimated environmental variance components of fruit ripening date measured by days in a Japanese pear (Pyrus pyrifolia Nakai) breeding field in the National Institute of Fruit Tree Science, Tsukuba, Ibaraki, Japan. We estimated variance among fruits within a tree (σf2) as 25.6, among trees within a genotype (σt2) as 0.2, among years (σy2) as 9.4, associated with genotype × year interaction (σgy2) as 7.9, and associated with tree × year interaction (σty2) as 1.2. Because σf2 was the largest environmental variance component, increasing the number of fruit evaluated would most effectively reduce the environmental variance, and tree replication would not because of very small σt2 and σty2. The 95% confidence limit of a genotypic value was ± 10 days in the evaluation of five fruits on a single tree in a year and ± 7 days over 2 years. Broad-sense heritability in a family, each offspring in which was evaluated using five fruits on a single tree in a single year, was estimated at 0.83 for three full-sib families analyzed.

Validation of molecular markers associated with fruit ripening day of Japanese pear (Pyrus pyrifolia Nakai) using variance components

2016 ◽  
Vol 199 ◽  
pp. 9-14 ◽  
Author(s):  
Sogo Nishio ◽  
Takeshi Hayashi ◽  
Toshiya Yamamoto ◽  
Masahiko Yamada ◽  
Norio Takada ◽  
...  
Keyword(s):  
Molecular Markers ◽  
Fruit Ripening ◽  
Variance Components ◽  
Japanese Pear ◽  
Pyrus Pyrifolia ◽  
Pyrus Pyrifolia Nakai

What contributes to differences in phenotypic variation between generations?

2009 ◽  
Vol 2009 ◽  
pp. 200-200
Author(s):  
A Wolc ◽  
I White ◽  
M Lisowski ◽  
W G Hill
Keyword(s):  
Animal Model ◽  
Environmental Effects ◽  
Environmental Conditions ◽  
Phenotypic Variation ◽  
Variance Components ◽  
Genetic Variance ◽  
Phenotypic Variance ◽  
Base Population ◽  
Substantial Heterogeneity ◽  
Over Time

Under the animal model genetic variance is estimated in the base population taking into account inbreeding and is otherwise assumed to remain unchanged over generations. In practice, phenotypic variation differs randomly or systematically over time. Intuitively, such changes would be attributed mostly to environmental effects, and so lower heritability would be expected when variation is inflated. Studies in dairy cattle show contradictory results (e.g. Boldman and Freeman, 1990). Laying hens are kept under environmental conditions intended to be constant, but show substantial heterogeneity in phenotypic variance (VP) over generations. The aim was to investigate how variance components change.

scholarly journals Molecular Cloning of β-Galactosidase from Japanese Pear (Pyrus pyrifolia) and its Gene Expression with Fruit Ripening

2001 ◽  
Vol 42 (5) ◽  
pp. 492-498 ◽  
Author(s):  
Akira Tateishi ◽  
Hiroaki Inoue ◽  
Hajime Shiba ◽  
Shohei Yamaki
Keyword(s):  
Gene Expression ◽  
Molecular Cloning ◽  
Fruit Ripening ◽  
Japanese Pear ◽  
Pyrus Pyrifolia ◽  
Its Gene

scholarly journals Genotypic Variation in and Environmental Variance Components of Sugar Composition in Japanese Pear Fruit

HortScience ◽  
2019 ◽  
Vol 54 (9) ◽  
pp. 1465-1469
Author(s):  
Toshihiro Saito ◽  
Norio Takada ◽  
Hidenori Kato ◽  
Shingo Terakami ◽  
Sogo Nishio
Keyword(s):  
Variance Components ◽  
Fruit Juice ◽  
Sugar Content ◽  
Genotypic Variation ◽  
Phenotypic Selection ◽  
Japanese Pear ◽  
Sugar Composition ◽  
Pear Fruit ◽  
Environmental Variance ◽  
Total Sugar Content

Genotypic variations in and environmental variance components of the total sugar content (TSC) and sugar composition, including sucrose (SUC), fructose (FRU), glucose (GLU), and sorbitol (SOR), in the fruit juice of 13 Japanese pear cultivars were analyzed. The TSC of ‘Kanta’ and TSC of ‘Hoshiakari’ were high (both >14.5 g/100 mL). The contents of SUC and FRU were higher than those of the other sugars. The SUC contents were ranked as follows: ‘Gold Nijisseiki’, 7.3 g/100 mL; ‘Shuurei’, 6.2 g/100 mL; and ‘Akizuki’, 6.1 g/100 mL. The FRU content in ‘Kanta’ was the highest among all monomeric sugars evaluated (6.8 g/100 mL). These results suggest that ‘Kanta’ is superior in terms of both TSC and sugar composition, which determine sweetness. The yearly environmental variance components were negligible for all traits. The genotype × year ranged from 4.4% to 13.7% of the total variance. Within-tree variance was 17.1% for TSC, whereas that for the sugar composition ranged from 1.4% to 6.1%. The tree × year ranged from 2.7% to 7.4%. Variance among fruits within trees was the largest environmental variance component—except for FRU—and ranged from 8.8% to 35.6%. Broad-sense heritability (hB2) values based on single tree, single year, and single fruit measurements were 0.33, 0.64, 0.69, 0.71, and 0.76 for TSC, SUC, FRU, GLU, and SOR, respectively. These results suggest that it would be easier to estimate genetic differences in sugar components with a higher level of precision than those in TSC. Increasing the fruit number up to five, in combination with yearly repetition increased to two (without tree repetition), significantly increased the hB2 of all traits undergoing study. The information obtained during this study will be useful for improving the accuracy of phenotypic selection and future genomic-based breeding studies performed to improve the sweetness of Japanese pear fruits.

Estimation of additive and dominance genetic variance components for female fertility traits in Iranian Holstein cows

2018 ◽  
Vol 156 (4) ◽  
pp. 565-569
Author(s):  
H. Ghiasi ◽  
R. Abdollahi-Arpanahi ◽  
M. Razmkabir ◽  
M. Khaldari ◽  
R. Taherkhani
Keyword(s):  
Dairy Cows ◽  
Variance Components ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Genetic Effects ◽  
Information Criteria ◽  
Phenotypic Variance ◽  
Dominance Variance ◽  
Dominance Genetic Variance ◽  
Estimated Heritability

AbstractThe aim of the current study was to estimate additive and dominance genetic variance components for days from calving to first service (DFS), a number of services to conception (NSC) and days open (DO). Data consisted of 25 518 fertility records from first parity dairy cows collected from 15 large Holstein herds of Iran. To estimate the variance components, two models, one including only additive genetic effects and another fitting both additive and dominance genetic effects together, were used. The additive and dominance relationship matrices were constructed using pedigree data. The estimated heritability for DFS, NSC and DO were 0.068, 0.035 and 0.067, respectively. The differences between estimated heritability using the additive genetic and additive-dominance genetic models were negligible regardless of the trait under study. The estimated dominance variance was larger than the estimated additive genetic variance. The ratio of dominance variance to phenotypic variance was 0.260, 0.231 and 0.196 for DFS, NSC and DO, respectively. Akaike's information criteria indicated that the model fitting both additive and dominance genetic effects is the best model for analysing DFS, NSC and DO. Spearman's rank correlations between the predicted breeding values (BV) from additive and additive-dominance models were high (0.99). Therefore, ranking of the animals based on predicted BVs was the same in both models. The results of the current study confirmed the importance of taking dominance variance into account in the genetic evaluation of dairy cows.

The Changes in Genetic and Environmental Variance With Inbreeding in Drosophila melanogaster

Genetics ◽  
1999 ◽  
Vol 152 (1) ◽  
pp. 345-353 ◽  
Author(s):  
Michael C Whitlock ◽  
Kevin Fowler
Keyword(s):  
Drosophila Melanogaster ◽  
Large Scale ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Inbred Lines ◽  
Residual Variance ◽  
Phenotypic Variance ◽  
Population Bottlenecks ◽  
Environmental Variance ◽  
Components Of Variance

Abstract We performed a large-scale experiment on the effects of inbreeding and population bottlenecks on the additive genetic and environmental variance for morphological traits in Drosophila melanogaster. Fifty-two inbred lines were created from the progeny of single pairs, and 90 parent-offspring families on average were measured in each of these lines for six wing size and shape traits, as well as 1945 families from the outbred population from which the lines were derived. The amount of additive genetic variance has been observed to increase after such population bottlenecks in other studies; in contrast here the mean change in additive genetic variance was in very good agreement with classical additive theory, decreasing proportionally to the inbreeding coefficient of the lines. The residual, probably environmental, variance increased on average after inbreeding. Both components of variance were highly variable among inbred lines, with increases and decreases recorded for both. The variance among lines in the residual variance provides some evidence for a genetic basis of developmental stability. Changes in the phenotypic variance of these traits are largely due to changes in the genetic variance.

scholarly journals Estimation of Additive and Dominance Genetic Effects on Body Weight, Carcass and Ham Quality Traits in Heavy Pigs

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 481
Author(s):  
Valentina Bonfatti ◽  
Roberta Rostellato ◽  
Paolo Carnier
Keyword(s):  
Variance Components ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Model Fitting ◽  
Genetic Effects ◽  
Phenotypic Variance ◽  
Genetic Response ◽  
Dominance Variance ◽  
Dry Cured Ham ◽  
Genetic Evaluations

Neglecting dominance effects in genetic evaluations may overestimate the predicted genetic response achievable by a breeding program. Additive and dominance genetic effects were estimated by pedigree-based models for growth, carcass, fresh ham and dry-cured ham seasoning traits in 13,295 crossbred heavy pigs. Variance components estimated by models including litter effects, dominance effects, or both, were compared. Across traits, dominance variance contributed up to 26% of the phenotypic variance and was, on average, 22% of the additive genetic variance. The inclusion of litter, dominance, or both these effects in models reduced the estimated heritability by 9% on average. Confounding was observed among litter, additive genetic and dominance effects. Model fitting improved for models including either the litter or dominance effects, but it did not benefit from the inclusion of both. For 15 traits, model fitting slightly improved when dominance effects were included in place of litter effects, but no effects on animal ranking and accuracy of breeding values were detected. Accounting for litter effects in the models for genetic evaluations would be sufficient to prevent the overestimation of the genetic variance while ensuring computational efficiency.

scholarly journals Genetic Differences and Environmental Variations in Calyx-end Fruit Cracking among Japanese Persimmon Cultivars and Selections

HortScience ◽  
2002 ◽  
Vol 37 (1) ◽  
pp. 164-167 ◽  
Author(s):  
Masahiko Yamada ◽  
Akihiko Sato ◽  
Yasuo Ukai
Keyword(s):  
Variance Components ◽  
Mean Value ◽  
Diospyros Kaki ◽  
Square Root ◽  
Environmental Variance ◽  
Japanese Persimmon ◽  
Single Tree ◽  
Fruit Cracking ◽  
Environmental Variations ◽  
The Mean

Environmental variance components were estimated for calyx-end fruit cracking in pollination-constant and nonastringent cultivars and selections of Japanese persimmon (Diospyros kaki Thunb.). The cracking value of a tree in a cultivar or selection (genotype) (X) was evaluated as the number of fruit that cracked divided by the total number (25) of fruit evaluated from each tree. Because the mean value of X was correlated with the variance of X, analyses of variance were performed using its square root value. The variance associated with genotyp× year interaction was the largest of environmental variance components. The variances associated among years and among trees within genotypes were very small. The mean percentage of cracked fruit in evaluation for 10 years was 3% for `Fuyu', 11% for `Matsumotowase-Fuyu', and 12% for `Izu'. On the basis of the environmental variance components obtained, it is proposed that all offspring genotypes exhibiting a phenotypic cracking incidence of less than 20% and 11% should be selected in single-year and three-year evaluations, respectively, when those genotypes are evaluated using 25 fruits from a single tree, in order to successfully select all genotypes with an genotypic incidence of less than 3%.

Genotype by environment interactions in lamb weight and carcass composition traits

2002 ◽  
Vol 75 (1) ◽  
pp. 3-14 ◽  
Author(s):  
N. Maniatis ◽  
G. E. Pollott
Keyword(s):  
Variance Components ◽  
Mixed Model ◽  
Genotype By Environment Interaction ◽  
Carcass Composition ◽  
Phenotypic Variance ◽  
Environment Interaction ◽  
Additive Effects ◽  
Environmental Variance ◽  
Genotype By Environment Interactions ◽  
Genotype By Environment

AbstractThe systematic use of the same genotype in several different environments provides information that can be used to estimate genotype by environment interaction (G ✕ E) variances and parameters. Data from the UK Suffolk Sire Referencing Scheme Ltd were used to investigate a range of sire and dam by environment interactions in lamb weight (at 8 weeks and scanning) and body composition traits (muscle and fat depth). These interactions were calculated in a DFREML mixed model containing direct additive, maternal additive, maternal environmental random variance components and the covariance between direct and maternal additive effects. Sire interactions with year, flock and flock-year and dam effects within and between litters were investigated. The addition of all G ✕ E (co)variance components resulted in an improved fit of the model for all traits. Sire interactions accounted for between 2 and 3% of the phenotypic variance in all traits, usually at the expense of both additive effects. Maternal litter environmental variance components ranged from 10% (fat depth and muscle depth) to 20% (8-week weight) of phenotypic variance. Most of this variation was found in the residual component of variance when the term was omitted from the model. When fitting sire G✕ E components in a model the covariance between direct and maternal additive genetic effects, as a proportion of phenotypic variance, was reduced to a low level (from –0·36 to –0·08 for 8-week weight). Genotype by environment interactions form a significant source of variation in lamb growth and composition traits and reduce the high negative correlation between additive effects found previously in these traits.

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