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Oliveira, Leticia F., Luiz F. F. Brito, Jay S. Johnson, and Renata Veroneze. "PSXII-3 Including Non-Additive Genetic Effects in Genomic Prediction and Estimation of Variance Components for Performance and Heat Stress Traits in Pigs." Journal of Animal Science 101, Supplement_3 (November 6, 2023): 345–46. http://dx.doi.org/10.1093/jas/skad281.410.
Повний текст джерелаАнотація:
Abstract Non-additive genetic effects may have important roles in the phenotypic expression of performance and adaptation traits in livestock. Therefore, we aimed to evaluate the inclusion of non-additive genetic effects in genomic prediction models and variance component estimation of performance traits in a purebred pig population and heat tolerance indicators in a crossbred pig population. The first dataset consisted of 3,534 individuals with genotypes for 52,843 SNPs and five pre-adjusted phenotypes from a public database of a purebred pig line. Twelve models fitting or not dominance and/or epistasis effects (additive-by-additive, additive-by-dominance, and dominance-by-dominance) and inbreeding were used to estimate variance components. Prediction ability was assessed based on 10-fold cross-validation and the bias, dispersion, and accuracy estimates were computed based on the LR method. We also evaluated the impact of including non-additive genetic effects on the ranking of the animals’ breeding value and in the proportion of commonly selected individuals. The second dataset consisted of records from 1,645 lactating sows (Large White x Landrace cross) genotyped for 50,703 SNPs and traits related to heat stress response: skin temperature (ear, shoulder, rump, and tail), vaginal temperature measured every 10 minutes, and the average of the six records per hour corresponding to 08:00, 12:00, 16:00, and 20:00 hours during four days; respiration rate, panting score (PS; score scale from 0 to 3), and hair density (HD, score scale from 0 to 2). Four models including or not, inbreeding and the effect of dominance and additive-by-additive epistasis were used to estimate variance components. There was no effect on residual variance estimates due to the inclusion of non-additive genetic effects in the models for most traits. However, non-additive genetic effects reduced additive variance estimates, especially when additive-by-additive epistasis was fitted. Including non-additive genetic effects in the model did not improve the prediction accuracy of breeding values for purebreds, but there was a substantial change in the ranking of the animals and in the proportion of commonly selected individuals. For the crossbred traits, small non-additive genetic variance with large standard error estimates were obtained. Nevertheless, PS and HD presented notable additive-by-additive epistatic variance. PS presented h2aa estimates of 0.15 and additive-by-additive epistasis corresponding to 86.76% of the total genetic variance, while HD presented additive-by-additive epistatic heritability (h2aa) estimates from 0.46 to 0.49 and the proportion of total genetic variance explained by additive-by-additive epistasis ranged from 66.91% to 71.87%. In conclusion, including non-additive genetic effects did not improve the accuracy of prediction of breeding values for purebreds, but it changed the ranking of animals and selection decisions. Although PS and HD had large additive-by-additive epistasis effects, most of the traits related to heat stress in the crossbred population did not present relevant non-additive genetic effects.
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Pessoa, Angela Maria dos S., Elizanilda R. do Rêgo, and Maílson M. do Rêgo. "Additive and non-additive genetic effects for fruit traits of ornamental pepper." Horticultura Brasileira 39, no. 1 (March 2021): 39–45. http://dx.doi.org/10.1590/s0102-0536-20210106.
Повний текст джерелаАнотація:
ABSTRACT Pepper plants can be used as ornamental ones due to the contrasting traits of plants, flowers, and especially fruits. This variability can be exploited in genetic improvement programs aiming at identifying superior genotypes and obtaining hybrids. This work aimed to select parental and hybrid individuals through diallel analysis for fruit traits in Capsicum annuum. Seven pepper genotypes were crossed, and eleven fruit-related quantitative traits were evaluated. The data were subjected to diallel analysis using Griffing’s Method 1 (fixed model). There was a predominance of additive genetic effects on the fruit traits of ornamental pepper plants. Genotypes UFPB77.3 and UFPB390 are indicated as parents for the improvement of ornamental pepper plants, for fruit traits. Hybrids UFPB77.3 x UFPB099, UFPB390 x UFPB77.3, UFPB390 x UFPB001, UFPB390 x UFPB099, UFPB134 x UFPB77.3, and UFPB134 x UFPB390 present a potential for the production of hybrids and generation of segregating populations of ornamental peppers.
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Guillenea, Ana, Mario Lema, Diego Gimeno, Olga Ravagnolo, and Ana Carolina Espasandín. "Additive and non-additive effects for mature weight in beef cattle." Archivos Latinoamericanos de Producción Animal 28, no. 1-2 (October 27, 2020): 19–28. http://dx.doi.org/10.53588/alpa281204.
Повний текст джерелаАнотація:
Selection has emphasized animal growth, leading to an increase in their mature size affecting in some cases the pregnancy of the cows and the efficiency of the systems. Usually, crossbreeding improve productivity because of the genetic effects that the cows exploit, but the impact on mature weight (MW) has not been studied. The present study aimed at estimating MW and genetic parameters associated with the MW in crosses between two British breeds: Hereford (H/H) and Angus (A/A), a Continental: Salers (S/S), and a Zebu: Nelore (N/N). MW was analyzed at 4; 4.5; 5; 5.5 and 6 years of age using a repeated-measure sire model. For parameters estimation, an additive – dominant model was used including the fixed effects of breed group, contemporary group, and age as covariate linear and quadratic, with the linear regression fitted by breed group. Permanent environmental and sire were included as random effects. According to the results, it is expected to observe heterosis between H/H and N/N, however, the structure of the data may not be enough for estimate accurately the genetic parameters in this trait. The A/H, N/H, S/H, S/SH and H/NH cows were heavier than the H/H cows. All the breed groups continue gaining weight until six years of age. The results revealed that British crossbred animals are heavier than H/H at the first crossing but not in the following. Crossbred cows with proportions of 0.5 and greater for the Continental breed are heavier than H/H cows. Crosses between British and Zebu cows have higher mature weight than H/H at the first crossing and in backcrosses toward the British in all ages.
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Yadav, Seema, Xianming Wei, Priya Joyce, Felicity Atkin, Emily Deomano, Yue Sun, Loan T. Nguyen, et al. "Improved genomic prediction of clonal performance in sugarcane by exploiting non-additive genetic effects." Theoretical and Applied Genetics 134, no. 7 (April 26, 2021): 2235–52. http://dx.doi.org/10.1007/s00122-021-03822-1.
Повний текст джерелаАнотація:
Abstract Key message Non-additive genetic effects seem to play a substantial role in the expression of complex traits in sugarcane. Including non-additive effects in genomic prediction models significantly improves the prediction accuracy of clonal performance. Abstract In the recent decade, genetic progress has been slow in sugarcane. One reason might be that non-additive genetic effects contribute substantially to complex traits. Dense marker information provides the opportunity to exploit non-additive effects in genomic prediction. In this study, a series of genomic best linear unbiased prediction (GBLUP) models that account for additive and non-additive effects were assessed to improve the accuracy of clonal prediction. The reproducible kernel Hilbert space model, which captures non-additive genetic effects, was also tested. The models were compared using 3,006 genotyped elite clones measured for cane per hectare (TCH), commercial cane sugar (CCS), and Fibre content. Three forward prediction scenarios were considered to investigate the robustness of genomic prediction. By using a pseudo-diploid parameterization, we found significant non-additive effects that accounted for almost two-thirds of the total genetic variance for TCH. Average heterozygosity also had a major impact on TCH, indicating that directional dominance may be an important source of phenotypic variation for this trait. The extended-GBLUP model improved the prediction accuracies by at least 17% for TCH, but no improvement was observed for CCS and Fibre. Our results imply that non-additive genetic variance is important for complex traits in sugarcane, although further work is required to better understand the variance component partitioning in a highly polyploid context. Genomics-based breeding will likely benefit from exploiting non-additive genetic effects, especially in designing crossing schemes. These findings can help to improve clonal prediction, enabling a more accurate identification of variety candidates for the sugarcane industry.
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Taye, Shambel, and Mahilet Dawit. "Additive and Non-additive Genetic Effects on Growth and Egg Production Performance of Crossbred Chicken in Ethiopia." International Journal of Animal Science and Technology 8, no. 4 (November 28, 2024): 106–11. https://doi.org/10.11648/j.ijast.20240804.13.
Повний текст джерелаАнотація:
The present review article aims to provide an overview of the additive and non-additive genetic effects of crossbreeding and their contribution to the improvement of growth and egg production traits in chickens. It discusses the advancement in crossbreeding effects and mating design contribution to a significant rate of genetic progress in indigenous chicken. In Ethiopia, crossbreeding practice may be used to enhance the performance of local chicken ecotypes. The article extensively reviews various papers related to crossbreeding trials conducted in Ethiopia, evaluating their effectiveness in improving growth and egg production. It discusses the mating design and breeds used in these programs, such as exotic breeds like Rhode Island Red, Fayoumi, White Leghorn, Koekoek, Sasso, Kuroiler, and local Ethiopian chicken ecotypes. Among the exotic breeds involved in crossbreeding, Rhode Island Red and Sasso are considered more favorable for improving growth rate and color preference, while White Leghorn is preferred for enhancing egg production traits. In opposite to these indigenous chickens are preferred for disease resistance and product quality. Additive genetic effects are typically responsible for the genetic improvement of traits over generations through selection. In egg production, additive genetic effects influence the overall capacity of a chicken to lay eggs, affecting traits like egg number and egg size. Whereas, In growth performance, additive genetic effects influence traits like body weight gain, feed conversion efficiency, and overall growth rate. Non-additive genetic effects include dominance and epistatic interactions between genes. These effects can lead to genetic heterogeneity and can impact traits like egg production and growth performance besides playing a role in hybrid vigor or heterosis. In conclusion, both additive and non-additive genetic effects play a crucial role in determining egg production and growth performance in chickens. Additive effects drive genetic improvement over generations, while non-additive effects provide immediate benefits like hybrid vigor. Understanding and utilizing both types of genetic effects is essential for enhancing these traits in poultry breeding programs. Chicken crossbreeding programs are highly important in the poultry industry as they continuously improve the genetic potential of chickens, leading to more efficient production systems and higher profitability for producers.
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de Almeida Filho, Janeo Eustáquio, João Filipi Rodrigues Guimarães, Fabyano Fonsceca e Silva, Marcos Deon Vilela de Resende, Patricio Muñoz, Matias Kirst, and Marcio Fernando Ribeiro de Resende Júnior. "Genomic Prediction of Additive and Non-additive Effects Using Genetic Markers and Pedigrees." G3: Genes|Genomes|Genetics 9, no. 8 (July 1, 2019): 2739–48. http://dx.doi.org/10.1534/g3.119.201004.
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Barbosa, Leandro, Paulo Sávio Lopes, Adair José Regazzi, Robledo de Almeida Torres, Mário Luiz Santana Júnior, and Renata Veroneze. "Estimation of variance components, genetic parameters and genetic trends for litter size of swines." Revista Brasileira de Zootecnia 39, no. 10 (October 2010): 2155–59. http://dx.doi.org/10.1590/s1516-35982010001000008.
Повний текст джерелаАнотація:
Records of Large White breed animals were used to estimate variance components, genetic parameters and trends for the character total number of born piglets (TNBP) as measure of litter size. For obtaining variance components and genetic parameters, it was used the Restricted Maximum Likelihood Method using MTDFREML software. Two mixed models (additive and repeatability) were evaluated. The additive model contained fixed effect of the contemporary group and the following random effects: direct additive genetic and residual effect for the first parturition. Repeatability model had the same effects of the additive model plus parturition order fixed effect and non-correlated animal permanent environment random effect for the second, third and forth parturition. Direct additive heritability estimates for TNBP were 0.15 and 0.20 for the additive and repeatability models, respectively. The estimate of the ration among variance of the non-correlated effect of animal permanent environment effect and the phenotypic variance, expressed as total variance proportion (c2) was 0.09. The estimates of yearly genetic trends obtained in the additive and repeatability models have similar behaviors (0.02 piglets/sow/year).
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Cui, Leilei, Bin Yang, Nikolas Pontikos, Richard Mott, and Lusheng Huang. "ADDO: a comprehensive toolkit to detect, classify and visualize additive and non-additive quantitative trait loci." Bioinformatics 36, no. 5 (November 25, 2019): 1517–21. http://dx.doi.org/10.1093/bioinformatics/btz786.
Повний текст джерелаАнотація:
Abstract Motivation During the past decade, genome-wide association studies (GWAS) have been used to map quantitative trait loci (QTLs) underlying complex traits. However, most GWAS focus on additive genetic effects while ignoring non-additive effects, on the assumption that most QTL act additively. Consequently, QTLs driven by dominance and other non-additive effects could be overlooked. Results We developed ADDO, a highly efficient tool to detect, classify and visualize QTLs with additive and non-additive effects. ADDO implements a mixed-model transformation to control for population structure and unequal relatedness that accounts for both additive and dominant genetic covariance among individuals, and decomposes single-nucleotide polymorphism effects as either additive, partial dominant, dominant or over-dominant. A matrix multiplication approach is used to accelerate the computation: a genome scan on 13 million markers from 900 individuals takes about 5 h with 10 CPUs. Analysis of simulated data confirms ADDO’s performance on traits with different additive and dominance genetic variance components. We showed two real examples in outbred rat where ADDO identified significant dominant QTL that were not detectable by an additive model. ADDO provides a systematic pipeline to characterize additive and non-additive QTL in whole genome sequence data, which complements current mainstream GWAS software for additive genetic effects. Availability and implementation ADDO is customizable and convenient to install and provides extensive analytics and visualizations. The package is freely available online at https://github.com/LeileiCui/ADDO. Supplementary information Supplementary data are available at Bioinformatics online.
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Kelleher, M. M., F. Buckley, R. D. Evans, and D. P. Berry. "Additive genetic, non-additive genetic and permanent environmental effects for female reproductive performance in seasonal calving dairy females." Irish Journal of Agricultural and Food Research 55, no. 1 (June 1, 2016): 10–23. http://dx.doi.org/10.1515/ijafr-2016-0002.
Повний текст джерелаАнотація:
AbstractExcellent reproductive performance (i.e. 365-day calving interval) is paramount to herd profit in seasonal-calving dairy systems. Reproductive targets are currently not being achieved in Irish dairy herds. Furthermore, most research on the genetics of reproductive performance in dairy cattle has focused primarily on lactating cows and relatively few studies have attempted to quantify the genetic contribution to differences in reproductive performance in nulliparae. The objective of the present study was to estimate the contribution of both the additive and non-additive genetic components, as well as the permanent environmental component, to phenotypic variation in the reproductive traits in nulliparous, primiparous and multiparous seasonal-calving dairy females. Reproductive phenotypes were available on up to 202,525 dairy females. Variance components were estimated using (repeatability where appropriate) linear animal mixed models; fixed effects included in the mixed models were contemporary group, parity (where appropriate), breed proportion, inter-breed specific heterosis coefficients and inter-breed specific recombination loss coefficients. Heritability of the reproductive traits ranged from 0.004 (pregnancy rate to first service) to 0.17 (age at first service in nulliparae), while repeatability estimates for the reproductive traits in cows ranged from 0.01 (calving interval) to 0.11 (pregnant in the first 42 days of the breeding season). Breed-specific heterosis regression coefficients suggest that, relative to the parental mean, a first-cross Holstein–Jersey crossbred was almost 7 days younger at first calving, had a 9-day shorter calving interval, a 6 percentage unit greater pregnancy rate in the first 42 days of the breeding season and a 3 percentage unit greater survival rate to next lactation. Heifer calving rate traits were strongly genetically correlated with age at first calving (–0.97 to –0.66) and calving rate in the first 42 days of the calving season for first parity cows (0.77 to 0.56), but genetic correlations with other cow reproductive traits were weak and inconsistent. Calving interval was strongly genetically correlated with the majority of the cow traits; 56%, 40%, and 92% of the genetic variation in calving interval was explained by calving to the first service interval, number of services and pregnant in the first 42 days of the breeding season, respectively. Permanent environmental correlations between the reproductive performance traits were generally moderate to strong. The existence of contributions from non-additive genetic and permanent environmental effects to phenotypic differences among cows suggests the usefulness of such information to rank cows on future expected performance; this was evidenced by a stronger correlation with future reproductive performance for an individual cow index that combined additive genetic, non-additive genetic and permanent environmental effects compared to an index based solely on additive genetic effects (i.e. estimated breeding values).
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GIANOLA, DANIEL, and GUSTAVO de los CAMPOS. "Inferring genetic values for quantitative traits non-parametrically." Genetics Research 90, no. 6 (December 2008): 525–40. http://dx.doi.org/10.1017/s0016672308009890.
Повний текст джерелаАнотація:
SummaryInferences about genetic values and prediction of phenotypes for a quantitative trait in the presence of complex forms of gene action, issues of importance in animal and plant breeding, and in evolutionary quantitative genetics, are discussed. Current methods for dealing with epistatic variability via variance component models are reviewed. Problems posed by cryptic, non-linear, forms of epistasis are identified and discussed. Alternative statistical procedures are suggested. Non-parametric definitions of additive effects (breeding values), with and without employing molecular information, are proposed, and it is shown how these can be inferred using reproducing kernel Hilbert spaces regression. Two stylized examples are presented to demonstrate the methods numerically. The first example falls in the domain of the infinitesimal model of quantitative genetics, with additive and dominance effects inferred both parametrically and non-parametrically. The second example tackles a non-linear genetic system with two loci, and the predictive ability of several models is evaluated.
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Cunha, Elizângela Emídio, Ricardo Frederico Euclydes, Paulo Sávio Lopes, Robledo de Almeida Torres, and Paulo Luiz Souza Carneiro. "Behavior of genetic (co)variance components in populations simulated from non-additive genetic models of dominance and overdominance." Revista Brasileira de Zootecnia 39, no. 9 (September 2010): 1952–60. http://dx.doi.org/10.1590/s1516-35982010000900013.
Повний текст джерелаАнотація:
The aim of this work was to investigate the short-term behavior of the genetic variability of quantitative traits simulated from models with additive and non-additive gene action in control and phenotypic selection populations. Both traits, one with low (h² = 0.10) and the other with high (h² = 0.60) heritability, were controlled by 600 biallelic loci. From a standard genome, it was obtained six genetic models which included the following: only the additive gene effects; complete and positive dominance for 25, 50, 75 and 100% of the loci; and positive overdominance for 50% of the loci. In the models with dominance deviation, the additive allelic effects were also included for 100% of the loci. Genetic variability was quantified from generation to generation using the genetic variance components. In the absence of selection, genotypic and additive genetic variances were higher. In the models with non-additive gene action, a small magnitude covariance component raised between the additive and dominance genetic effects whose correlation tended to be positive on the control population and negative under selection. Dominance variance increased as the number of loci with dominance deviation or the value of the deviation increased, implying on the increase in genotypic and additive genetic variances among the successive models.
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Guimarães, Patrik, Ana Letycia Basso Garcia, Carla Costa Garcia, David Evandro Fernandes, Thiago Romanos Benatti, Aurelio Aguiar, Jose Luis Lima, et al. "Genetic parameters for early growth and disease resistance in a cloned F2 hybrid progeny of Eucalyptus urophylla × grandis." Agrociencia Uruguay 27, NE2 (November 20, 2023): e1255. http://dx.doi.org/10.31285/agro.27.1255.
Повний текст джерелаАнотація:
The VERACEL breeding program includes several advanced generation urograndis hybrids (F2) from crosses of selected F1. To understand the performance and genetics of these F2, we established F2-cloned progeny trials with 1,350 clones from 35 families, each family with 8 to 35 cloned progenies. These families stem from crosses between known F1 urograndis female parents and pollen mixtures of other selected parents. The experimental design comprised 15 trials with 95 clones each, arranged in randomized blocks and linked by 7 common commercial hybrid clones. These experiments were performed in two sites contrasting for physiological disorder (PD) incidence. Due to incomplete pedigree of the families, the model fitted assumed the additive genetic relationship between sibs as half-sibs. The non-additive genetic component was estimated from clone effects within half-sib families. A multisite individual tree genetic model was fitted for diameter, height, PD, Calonectria, and rust incidence for trees up to 1 year old: yijklmn= µ+gi+gij+sm+cn+tbkl+sgim+sgijm+scmn+eijklmn; where random effects are gij (additive genetic effects), gi (all non-additive genetic effects of clones), and eijklmn (residuals); and fixed effects are sm, which is either site with higher or lower productivity and PD incidence, cn is F1 or F2, and tbkl is trial-block interaction. The same model was used for diseases and PD, but assumed a binomial distribution with a logit link function. PD was analysed only for the higher PD incidence site, thus excluding interactions with the other site. Results indicate that at the high PD incidence site, height and diameter growth was greater (~40%), but it also had higher mortality (40% vs. 22%) and higher PD incidence (51% vs. 23%). Compared with F1 controls, Calonectria incidence was higher in F2 (~10%) but similar at both sites, as was rust, although with lower incidence (~5%). Multisite analysis revealed low additive genetic variance and moderate total genetic variance (A+NA) for growth, diseases, and PD. For growth, narrow- and broad-sense heritability were h2=0.11 and H2=0.40. The additive genetic correlation between the two sites was close to 1 (rA~0.9), whereas the non-additive genetic correlation was lower (rNA~0.5). The narrow- and broad-sense heritability for diseases and PD was low (between 0.10 and 0.15). The low additive genetic variance for growth, diseases, and PD constrains substantial gains from parental selection within F1. However, clonal selection would still be effective due to considerable non-additive effects. Further studies using a large set of various populations are needed to validate these findings.
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Eaves, Lindon J., Andrew C. Heath, Michael C. Neale, John K. Hewitt, and Nicholas G. Martin. "Sex differences and non-additivity in the effects of genes on personality." Twin Research 1, no. 3 (June 1, 1998): 131–37. http://dx.doi.org/10.1375/twin.1.3.131.
Повний текст джерелаАнотація:
AbstractNew large-sample data show that non-additive genetic effects, probably epistatic interactions between loci, and sex-limited gene expression are significant features of the genetic architecture of human personality as measured by questionnaire scales of extraversion and neuroticism. Three large data sets – new data on large samples (n = 20 554) of US twins, their spouses, parents, siblings and children, correlations for Australian twins (n = 7 532), and previously published twin data from Finland (n = 14 288) – are subjected to an integrated analysis to test alternative hypotheses about the genetic causes of family resemblance in personality. When allowance is made for differences in reliability of the scales, the combined data are consistent with the same model for variation. There are significant amounts of genetic non-additivity for both dimensions of personality. The evidence favours additive × additive epistatic interactions rather than dominance. In the case of neuroticism, there is especially strong evidence of sex differences in genetic architecture favouring a greater relative contribution of non-additive genetic effects in males. The data confirm previous claims to find no major contribution of the shared environment of twins and siblings to these dimensions of personality. Correlations between spouses are zero, and the correlations for very large samples of siblings and non-identical twins do not differ significantly.
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Liljedahl, L. E., R. W. Fairfull, and R. S. Gowe. "Age-regulated expression of genetic and environmental variation in fitness traits. 1. Genetic effects and variances for egg production in a factorial mating of six selected Leghorn strains." Canadian Journal of Animal Science 79, no. 3 (September 1, 1999): 253–67. http://dx.doi.org/10.4141/a97-103.
Повний текст джерелаАнотація:
White Leghorn strains were crossed reciprocally in a complete factorial mating system producing 6 pure strains and 30 strain-crosses, which were kept in individual cages for two laying cycles, 133–496 and 547–909 d of age. The egg production in the second cycle (C2) of the various genotypes started about 10 – 20% lower and had a more linear and less persistent course than in the first cycle (C1). Strains exhibited very different patterns of age changes in both additive and non-additive genetic effects as well as in cytoplasmic effects. The additive autosomal and sex-linked genes (Ai and Zi) active in one laying cycle were quite different from those active in the other laying cycle as shown by low strain genetic correlations between their effects in C1 and C2. Further, the sets of Ai and Zi genes responded with effects quite opposite to each other in both C1 and C2 as indicated by highly negative strain genetic correlations between the Ai and Zi effects. The average non-additive genetic effect of sire strain i or dam strain j over all its crosses with other strains (hi) and the non-additive genetic effect due to the specific combination of genes occurring in each of the two reciprocal crosses between strain i and strain j (sij), showed very divergent patterns of age changes with a conspicuously greater divergence as age advanced. The overall non-additive genetic effect (mean heterosis) increased significantly with age across the two cycles. The strain crosses that most successfully maintained their rate of lay until the end of C2, also most successfully developed a rising age trend for total heterosis. The non-additive genes active in one laying cycle were significantly different from those active in the other laying cycle as shown by the moderately low strain genetic correlations between their effects in C1 and C2. The genotypic variance and its various components increased markedly with age, however, with a tendency to reach a plateau towards the end of both the first and the second laying cycle. The environmental variance increased parallel to the genotypic variance. Consequently, the phenotypic variance followed the same pattern of age changes. The results are discussed in relation to the theoretical aspects of ageing genetics. A model compatible with all the age trends of the genetic and environmental effects and variances is set up, assuming that ageing is composed of two main opposing forces. Finally, the results are briefly discussed from the animal breeding point of view. Key words: Ageing, fitness, laying hens, genetic effects, variation, expression
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ND, Vinay, RK Yadav, TK Behera, A. Talukdar, Suma Lata, and Anjan Das. "Generation mean analysis unveils genetic effects controlling major yield traits in okra [Abelmoschus esculentus (L.) Moench]." Vegetable Science 48, no. 02 (December 27, 2021): 164–71. http://dx.doi.org/10.61180/vegsci.2021.v48.i2.06.
Повний текст джерелаАнотація:
The present study on generation means analysis was carried out to uncover genetics of yield traits in okra. To determine the nature and magnitude of gene action six generations (P1, P2, F1, F2, BC1 and BC2) of cross Pusa Sawani x Pusa Bhindi- 5 was assessed. The results revealed that both additive and dominance gene effects were significant in genetic control of yield traits. However, the magnitude of dominance gene effects was significant and higher for seed germination per cent, days to first flower, node to first flower, number of fruiting nodes, plant height and fruit yield per plant. Therefore, heterosis breeding would be effective to improve these traits. Additive genetic effect was significant for days to 50 per cent flower, inter-nodal length, number of primary branches, fruit length, fruit diameter and fruit weight. Result of scaling tests confirmed the role of non-allelic interaction in genetic control of all the yield traits analysed. The opposite sign of dominance (h) and dominance x dominance interaction (l) for many yield traits suggested role of duplicate type of epistasis, while few characters exhibited complementary type of epistasis. For improving traits with higher fixable (additive and additive x additive) component of genetic variation, pedigree method of breeding would be useful. For traits showing significant values of both additive and non-additive gene effects, improvement can be done by either recurrent selection or bi-parental mating system in segregating generations followed by selection.
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Oakey, Helena, Arūnas Verbyla, Wayne Pitchford, Brian Cullis, and Haydn Kuchel. "Joint modeling of additive and non-additive genetic line effects in single field trials." Theoretical and Applied Genetics 113, no. 5 (August 2, 2006): 809–19. http://dx.doi.org/10.1007/s00122-006-0333-z.
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Oakey, Helena, Arūnas P. Verbyla, Brian R. Cullis, Xianming Wei, and Wayne S. Pitchford. "Joint modeling of additive and non-additive (genetic line) effects in multi-environment trials." Theoretical and Applied Genetics 114, no. 8 (April 11, 2007): 1319–32. http://dx.doi.org/10.1007/s00122-007-0515-3.
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Liu, Y., and P. K. Mathur. "Simplifications of marker-assisted genetic evaluation and accounting for non-additive interaction effects." Archives Animal Breeding 48, no. 5 (October 10, 2005): 460–74. http://dx.doi.org/10.5194/aab-48-460-2005.
Повний текст джерелаАнотація:
Abstract. A computing simplification was applied to marker-assisted genetic evaluation of quantitative traits including additive and non-additive effects of QTL as well as residual polygenic effects. Different situations including QTL and the residual polygenic effect estimated as a sum or separately, and with or without non-additive effects integrated in models were evaluated. The computing simplification was used in combinations with different models and parameterizations. An example data was adopted to illustrate the simplified computing strategy and was compared with the computing method of direct inversion. Identical results were obtained from both computing strategies. The main advantage of the simplification is that it does not require inversion of non-additive relationship matrices and relationship matrices of QTL, and the number of random effects in mixed model equations is the same as any animal model with only additive effects.
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Duenk, Pascal, Piter Bijma, Mario P. L. Calus, Yvonne C. J. Wientjes, and Julius H. J. van der Werf. "The Impact of Non-additive Effects on the Genetic Correlation Between Populations." G3: Genes|Genomes|Genetics 10, no. 2 (December 19, 2019): 783–95. http://dx.doi.org/10.1534/g3.119.400663.
Повний текст джерелаАнотація:
Average effects of alleles can show considerable differences between populations. The magnitude of these differences can be measured by the additive genetic correlation between populations (rg). This rg can be lower than one due to the presence of non-additive genetic effects together with differences in allele frequencies between populations. However, the relationship between the nature of non-additive effects, differences in allele frequencies, and the value of rg remains unclear, and was therefore the focus of this study. We simulated genotype data of two populations that have diverged under drift only, or under drift and selection, and we simulated traits where the genetic model and magnitude of non-additive effects were varied. Results showed that larger differences in allele frequencies and larger non-additive effects resulted in lower values of rg. In addition, we found that with epistasis, rg decreases with an increase of the number of interactions per locus. For both dominance and epistasis, we found that, when non-additive effects became extremely large, rg had a lower bound that was determined by the type of inter-allelic interaction, and the difference in allele frequencies between populations. Given that dominance variance is usually small, our results show that it is unlikely that true rg values lower than 0.80 are due to dominance effects alone. With realistic levels of epistasis, rg dropped as low as 0.45. These results may contribute to the understanding of differences in genetic expression of complex traits between populations, and may help in explaining the inefficiency of genomic trait prediction across populations.
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Mahdavi, M., G. R. Dashab, M. Vafaye Valeh, M. Rokouei, and M. Sargolzaei. "Genomic evaluation and variance component estimation of additive and dominance effects using single nucleotide polymorphism markers in heterogeneous stock mice." Czech Journal of Animal Science 63, No. 12 (December 4, 2018): 492–506. http://dx.doi.org/10.17221/83/2017-cjas.
Повний текст джерелаАнотація:
Exploration of genetic variance has mostly been limited to additive effects estimated using pedigree data and non-additive effects have been ignored. This study aimed to evaluate the performance of single nucleotide polymorphisms (SNPs) marker models in the mixed and orthogonal framework including both additive and non-additive effects for estimating variances and genomic prediction in four diabetes-related traits in heterogeneous stock mice. Models have performed differently in detecting SNPs affecting traits. Dominance variances explained over 14.7 and 3.8% of genetic and phenotype variance in a Genomic prediction and variance component estimation method (GVCBLUP) framework. Reliabilities of additive Genomic best linear unbiased prediction model (GBLUP) in different traits ranged from 44.8 to 66.6%, for GVCBLUPs framework including both additive and dominance effects (MAD), and 46.1 to 69% for the model including additive effect (MA). Dominance GBLUP reliabilities ranged from 6 to 26.4% for MAD and from 22.5 to 50.5% in the model including dominance (MD). MA and MD had higher reliability for additive and dominance GBLUPs compared to MAD. Reliabilities of GBLUPs in MAD and MA for all traits were not significant except for growth slope (P < 0.01). In orthogonal framework models, epistasis variances accounted for a greater proportion (87.3, 89.1, 95.5, and 77.2%) of genetic variation for end weight, growth slope, body mass index, and body length, respectively. Heritability in a broad sense was estimated at 1.12, 1.67, 3.64, and 2.0%, in which non-additive heritability had a significant contribution. Genetic variances explained by dominance using GVCBLUPs were 16.8, 29.4, 14.6, and 14.9% for the traits. Generally, the non-additive models had a lower value of deviance information criterion (DIC) and performed better in estimating the variance component. Comparing the estimated variance by orthogonal framework models confirmed the results previously estimated by GVCBLUPs, with the difference that the estimates were shrinking. Following significant SNPs affecting diabetes-related traits by post-genome-wide studies could reveal unknown aspects and contribute to genetic control of the disease.
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Zilhão, Nuno R., Dirk J. A. Smit, Anouk den Braber, Conor V. Dolan, Gonneke Willemsen, Dorret I. Boomsma, and Danielle C. Cath. "Genetic and Environmental Contributions to Stability in Adult Obsessive Compulsive Behavior." Twin Research and Human Genetics 18, no. 1 (December 18, 2014): 52–60. http://dx.doi.org/10.1017/thg.2014.77.
Повний текст джерелаАнотація:
This study investigates the relative contribution of genetic and environmental factors to the stability of obsessive-compulsive (OC) symptoms in an adult population-based sample. We collected data from twin pairs and their siblings, using the Padua Inventory Revised Abbreviated, from the population-based Netherlands Twin Register (NTR) in 2002 (n = 10.134) and 2008 (n = 15.720). Multivariate twin analyses were used to estimate the stability of OC symptoms as a function of genetic and environmental components. OC symptoms were found to be highly stable, with a longitudinal phenotypic correlation of 0.63. Longitudinal broad sense heritability was found to be 56.0%. Longitudinal correlations for genetic (r = 0.58 for additive, r = 1 for non-additive genetic factors) and non-shared environment (r = 0.46) reflected stable effects, indicating that both genes and environment are influencing the stability of OC symptoms in adults. For the first time, evidence is reported for non-additive genetic effects on the stability of OC symptoms. In conclusion, this study showed that OC symptoms are highly stable across time in adults, and that genetic effects contribute mostly to this stability, both in an additive and non-additive way, besides non-shared environmental factors. These data are informative with respect to adult sample selection for future genetic studies, and suggest that gene–gene interaction studies are needed to further understand the dominance effect found in this study.
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Bertoli, C. D., J. Braccini Neto, C. McManus, J. A. Cobuci, G. S. Campos, M. L. Piccoli, and V. Roso. "Modelling non-additive genetic effects using ridge regression for an Angus–Nellore crossbred population." Animal Production Science 59, no. 5 (2019): 823. http://dx.doi.org/10.1071/an17439.
Повний текст джерелаАнотація:
Data from 294045 records from a crossbred Angus × Nellore population were used to estimate fixed genetic effects (both additive and non-additive) and to test different non-additive models using ridge regression. The traits studied included weaning gain (WG), postweaning gain (PG), phenotypic scores for weaning (WC) and postweaning (PC) conformation, weaning (WP) and postweaning (PP) precocity, weaning (WM) and postweaning (PM) muscling and scrotal circumference (SC). All models were compared using the likelihood-ratio test. The model including all fixed genetic effects (breed additive and complementarity, heterosis and epistatic loss non-additive effects, both direct and maternal) was the best option to analyse this crossbred population. For the complete model, all effects were statistically significant (P < 0.01) for weaning traits, except the direct breed additive effects for WP and WM; direct complementarity effect for WP, WM, PP and PM and maternal epistatic loss for PG. Direct breed additive effect was positive for weaning traits and negative for postweaning. Maternal breed additive effect was negative for SC and WP. Direct complementarity and heterosis were positive for all traits and maternal complementarity and heterosis were also positive for all traits, except for PG. Direct and maternal epistatic loss effects were negative for all traits. We conclude that the fixed genetic effects are mostly significant. Thus, it is important to include them in the model when evaluating crossbred animals, and the model that included breed additive effects, complementarity, heterosis and epistatic loss differed significantly from all reduced models, allowing to infer that it was the best model. The model with only breed additive and heterosis was parsimonious and could be used when the structure or amount of data does not allow the use of complete model.
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Bertoli, Claudia Damo, Jose Braccini, Connie McManus, Jaime Araujo Cobuci, Elisandra Lurdes Kern, Mario Luiz Piccoli, Flavio Schenkel, and Vanerlei Roso. "Modeling breed additive and non-additive genetic effects using a Angus x Nellore crossbred population." Livestock Science 176 (June 2015): 1–13. http://dx.doi.org/10.1016/j.livsci.2015.03.020.
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Witting, K., P. Santtila, F. Rijsdijk, M. Varjonen, P. Jern, A. Johansson, B. von der Pahlen, K. Alanko, and N. K. Sandnabba. "Correlated genetic and non-shared environmental influences account for the co-morbidity between female sexual dysfunctions." Psychological Medicine 39, no. 1 (March 26, 2008): 115–27. http://dx.doi.org/10.1017/s0033291708003206.
Повний текст джерелаАнотація:
BackgroundPrevious studies have shown moderate heritability for female orgasm. So far, however, no study has addressed the pattern of genetic and environmental influences on diverse sexual dysfunctions in women, nor how genetic and environmental factors contribute to the associations between them.MethodThe sample was drawn from the Genetics of Sex and Aggression (GSA) sample and consisted of 6446 female twins (aged 18–43 years) and 1994 female siblings (aged 18–49 years). The participants responded to the Female Sexual Function Index (FSFI), either by post or online.ResultsModel fitting analyses indicated that individual differences on all six subdomains of the FSFI (desire, arousal, lubrication, orgasm, satisfaction, and pain) were primarily due to non-shared (individual-specific) environmental influences. Genetic influences were modest but significant, whereas shared environmental influences were not significant. A correlated factors model including additive and non-additive genetic and non-shared environmental effects proved to have the best fit and suggested that both correlated additive and non-additive genetic factors and unique environmental factors underlie the co-occurrence of the sexual function problems.ConclusionsThe findings suggest that female sexual dysfunctions are separate entities with some shared aetiology. They also indicate that there is a genetic susceptibility for sexual dysfunctions. The unique experiences of each individual are, however, the main factors determining if, and which, dysfunction develops.
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Werle, Amir José Klein, Fernando Rafael Alves Ferreira, Ronald José Barth Pinto, Claudete Aparecida Mangolin, Carlos Alberto Scapim, and Leandro Simões Azeredo Gonçalves. "Diallel analysis of maize inbred lines for grain yield, oil and protein content." Crop Breeding and Applied Biotechnology 14, no. 1 (March 2014): 23–28. http://dx.doi.org/10.1590/s1984-70332014000100004.
Повний текст джерелаАнотація:
This study aimed to investigate the combining ability and heterotic effects on grain yield (GY), oil content (OC) and crude protein (CP) in tropical and temperate maize lines. Hybrids and inbred lines were evaluated in a complete diallel scheme without reciprocals, in two experiments in randomized blocks with three replications. The partitioning of the sum of squares for general (GCA) and specific (SCA) combining ability indicated that both additive and non-additive effects were involved in the genetic control of the studied traits. The estimates of the quadratic components showed predominance of non-additive genetic effects in the trait control. However, for OC and CP, the non-additive effect had a clearly negative influence on the hybrid combinations. The cross L6x L10was considered promising, because it associated RG positively with BP and OC.
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Mota, Armando Dornelas, Camila Bastos Ribeiro, Regis de Castro Carvalho, and Flávia Maria Avelar Gonçalves. "Genetic Effects on Corn Seed Longevity." Journal of Agricultural Science 13, no. 2 (January 15, 2021): 56. http://dx.doi.org/10.5539/jas.v13n2p56.
Повний текст джерелаАнотація:
This study aimed to elucidate the maternal and paternal genetic effects of the physiological quality of hybrid seed corn over time, as well as the contribution of heterosis for this trait. The seeds of single hybrids, reciprocals and parents were obtained by manual crosses in a complete diallel cross scheme. The analyses of germination and accelerated aging were performed and the data were analyzed with Tukey test and Griffing method. The quadratic components of general combining ability were similar to the effects of specific combining ability and superior to reciprocal, in most evaluation periods, implying that the effects on seed quality characters were attributed to genes of additive effect and genes of non-additive effect. The maternal effect of corn seed longevity was highly significant however its contribution was smaller than general combining ability and specific combining ability effects, but proved to be important in combinations of parents with lower estimate of general combining ability.
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Joshi, Sivendra, Anil Kumar, Divya Chaudhary, Babita Bhatt, J. P. Jaiswal, Charu Bisht, Usha Pant, Banshidhar, Himanshu Prasad, and Tripti Tripathi. "Estimating the Inheritance Patterns of Peduncle length and Spike length in Bread Wheat (Triticum aestivum L. em Thell.)." Journal of Experimental Agriculture International 46, no. 7 (June 29, 2024): 807–14. http://dx.doi.org/10.9734/jeai/2024/v46i72633.
Повний текст джерелаАнотація:
Estimating the inheritance pattern of peduncle length and spike length in bread wheat is crucial for advancing research in wheat genetics and breeding. To understand this pattern an experiment was conducted using six generations of 4 crosses. This study investigated genetic parameters affecting peduncle and spike length in bread wheat across four families (A, B, C and D) using generation mean analysis. For peduncle length, the additive-dominance model was suitable for Family A, indicating significant dominance effects, while higher-order interactions were present in Families B, C, and D with dominance × dominance and additive × additive effects playing major roles. For spike length, digenic interaction models were appropriate for all families, highlighting significant dominance and dominance × dominance effects. Families A, B, and C showed prevalent duplicate epistasis, suggesting potential transgressive segregants. The findings suggest both additive and non-additive gene actions are crucial, indicating early and later generation selection strategies could be effective in improving these traits. Understanding the genetic variability and underlying genetic architecture of these traits can enhance wheat yield and quality, making them ideal targets for breeding programs aimed at improving productivity.
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Berguson, W. E., B. G. McMahon, and D. E. Riemenschneider. "Additive and Non-Additive Genetic Variances for Tree Growth in Several Hybrid Poplar Populations and Implications Regarding Breeding Strategy." Silvae Genetica 66, no. 1 (December 28, 2017): 33–39. http://dx.doi.org/10.1515/sg-2017-0005.
Повний текст джерелаАнотація:
Abstract Populus species (P. deltoides, P. maximowiczii, P. nigra) and their inter-specific hybrids were tested for growth rate over a five year period at four test locations in Minnesota, USA, to estimate genetic variance components. The breeding scheme incorporated recurrent selection of full-sib families of pure species parents, production of F1 inter-specific hybrids from selected families, and selection of clones within the F1s. Improvement of yield through time using this scheme is predicated on the assumption that additive effects comprise a significant portion of the total genetic variance. The estimates of additive and non-additive variances reported are not traditional point estimates, because a fully balanced mating design was impossible due to parental incompatibilities which result in incomplete breeding matrices. Instead, bounded estimates, not previously used in tree genetics research, are derived from linear combinations of formulae of genetic expectations observed among-family, among-clone, and environmental variances. Our results suggest that combined family and mass selection would lead to increases in growth rate of 27 % and 47 % per generation in P. deltoides and P. nigra, respectively. Broad sense-based clonal selection within the F1 could yield selection responses in excess of 90 % of the mean of such populations. Among-family variance comprised about 1/3 of total genetic variance while within-family variance was always about 2/3 of total genetic variance, regardless of pedigree. The results indicate that recurrent intraspecific selective breeding followed by interspecific hybridization and non-recurrent selection based on broad sense genetic variation would constitute an effective yield improvement strategy.
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Perotto, D., R. I. Cue, A. J. Lee, A. J. McAllister, J. R. Batra, C. Y. Lin, G. L. Roy, and J. M. Wauthy. "Additive and non-additive genetic effects of growth-curve parameters of Holstein, Ayrshire and crossbred females." Canadian Journal of Animal Science 74, no. 3 (September 1, 1994): 401–9. http://dx.doi.org/10.4141/cjas94-058.
Повний текст джерелаАнотація:
Crossbreeding parameters (line additive, dominance and additive × additive epistatic effects for individual and for maternal performance) on growth traits of females from a crossbreeding experiment between Holstein-based (HS) and Ayrshire-based (AS) lines were estimated by individual animal models, incorporating all known additive genetic relationships among animals, through restricted maximum likelihood and mixed-model methodologies. The growth traits [asymptotic weight (A), rate parameter (k), inflection parameter (m), average lifetime absolute growth rate (AGR), average lifetime absolute maturing rate (AMR) and average lifetime relative growth rate (RGR)] were estimated by fitting the Richards function to the observed growth curve of 3076 individuals. The statistical model included the random effect of the animal breeding value and the fixed effects of genetic group and station–year–season of birth. Results indicated that the HS exceeded (P < 0.001) the AS in additive effects for individual performance for both A and AGR. The HS exceeded (P < 0.05) the AS in additive effects for maternal performance for A. Individual heterosis was positive for A (P < 0.001) and for AGR (P < 0.01). Maternal heterosis was negative for A (P < 0.05) and positive for AMR (P < 0.05). Total heterosis (TH) had positive effects on both AGR and AMR (P < 0.05). Heterosis retained in advanced crossbred generations was not significant (P > 0.05) for any of the studied traits. The results suggest that crossbreeding designed to exploit TH can alter the shape of the growth curve of dairy cattle. Key words: Crossbreeding, dairy cattle, growth curve
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Jiang, Jicai, Shauneen O’Neill, Christian Maltecca, Justin Fix, Tamar Crum, Clint Schwab, and Francesco Tiezzi. "PSXII-12 Partitioning direct and maternal genetic effects into additive and non-additive components for growth and maternal traits in Yorkshire pigs." Journal of Animal Science 99, Supplement_3 (October 8, 2021): 251–52. http://dx.doi.org/10.1093/jas/skab235.459.
Повний текст джерелаАнотація:
Abstract This study investigates how much direct and maternal non-additive genetic effects contribute to growth and maternal traits in swine. We analyzed a sample of 19,475 genotyped Yorkshire pigs from Acuity Ag Solutions, LLC (Carlyle, IL). Approximately 50K SNPs were kept after quality control, and missing genotypes were then imputed using findhap.f90. The genotypes were used to construct genomic relationship matrices (GRMs) corresponding to additive (A), dominance (D), and additive-by-additive epistasis (E) effects for both direct and maternal effects. The GRMs were subsequently employed as covariance structure matrices in a linear mixed model consisting of eight random components, namely three direct genetic effects (Ad, Dd, and Ed), three maternal genetic effects (Am, Dm, and Em), maternal environmental effect, and common litter environmental effect. We estimated these variance components (VCs) for six growth traits (birth weight, average daily gain, back fat, and loin area) and six maternal traits of a sow (total number of piglets born, number of piglets born alive, average weight of piglets at birth, average weight of piglets weaned) using REML in MMAP (https://mmap.github.io/). As shown in Table 1, we found significant (P< 0.05) direct dominance and epistasis VCs for all six growth traits. Additionally, direct epistasis effects explained a larger proportion of phenotypic variation than direct dominance for all growth traits (0.04–0.12 vs. 0.01–0.04). In contrast, direct non-additive VCs were not significant for any maternal trait except for epistasis in average weight of piglets weaned. As for maternal non-additive effects, we only discovered significant additive VC in birth weight and average daily gain and significant epistasis VC in back fat (P< 0.05). Other maternal genetic VCs were largely negligible. In summary, direct dominance and epistasis effects play a prominent role in growth traits of Yorkshire pigs.
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Ishimori, Motoyuki, Hideki Takanashi, Kosuke Hamazaki, Yamato Atagi, Hiromi Kajiya-Kanegae, Masaru Fujimoto, Junichi Yoneda, Tsuyoshi Tokunaga, Nobuhiro Tsutsumi, and Hiroyoshi Iwata. "Dissecting the Genetic Architecture of Biofuel-Related Traits in a Sorghum Breeding Population." G3: Genes|Genomes|Genetics 10, no. 12 (October 13, 2020): 4565–77. http://dx.doi.org/10.1534/g3.120.401582.
Повний текст джерелаАнотація:
In sorghum [Sorghum bicolor (L.) Moench], hybrid cultivars for the biofuel industry are desired. Along with selection based on testcross performance, evaluation of the breeding population per se is also important for the success of hybrid breeding. In addition to additive genetic effects, non-additive (i.e., dominance and epistatic) effects are expected to contribute to the performance of early generations. Unfortunately, studies on early generations in sorghum breeding programs are limited. In this study, we analyzed a breeding population for bioenergy sorghum, which was previously developed based on testcross performance, to compare genomic selection models both trained on and evaluated for the per se performance of the 3rd generation S0 individuals. Of over 200 ancestral inbred accessions in the base population, only 13 founders contributed to the 3rd generation as progenitors. Compared to the founders, the performances of the population per se were improved for target traits. The total genetic variance within the S0 generation progenies themselves for all traits was mainly additive, although non-additive variances contributed to each trait to some extent. For genomic selection, linear regression models explicitly considering all genetic components showed a higher predictive ability than other linear and non-linear models. Although the number and effect distribution of underlying loci was different among the traits, the influence of priors for marker effects was relatively small. These results indicate the importance of considering non-additive effects for dissecting the genetic architecture of early breeding generations and predicting the performance per se.
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Chen, Zhi-Qiang, John Baison, Jin Pan, Johan Westin, Maria Rosario García Gil, and Harry X. Wu. "Increased Prediction Ability in Norway Spruce Trials Using a Marker X Environment Interaction and Non-Additive Genomic Selection Model." Journal of Heredity 110, no. 7 (October 2019): 830–43. http://dx.doi.org/10.1093/jhered/esz061.
Повний текст джерелаАнотація:
Abstract A genomic selection study of growth and wood quality traits is reported based on control-pollinated Norway spruce families established in 2 Northern Swedish trials at 2 locations using exome capture as a genotyping platform. Nonadditive effects including dominance and first-order epistatic interactions (including additive-by-additive, dominance-by-dominance, and additive-by-dominance) and marker-by-environment interaction (M×E) effects were dissected in genomic and phenotypic selection models. Genomic selection models partitioned additive and nonadditive genetic variances more precisely than pedigree-based models. In addition, predictive ability in GS was substantially increased by including dominance and slightly increased by including M×E effects when these effects are significant. For velocity, response to genomic selection per year increased up to 78.9/80.8%, 86.9/82.9%, and 91.3/88.2% compared with response to phenotypic selection per year when genomic selection was based on 1) main marker effects (M), 2) M + M×E effects (A), and 3) A + dominance effects (AD) for sites 1 and 2, respectively. This indicates that including M×E and dominance effects not only improves genetic parameter estimates but also when they are significant may improve the genetic gain. For tree height, Pilodyn, and modulus of elasticity (MOE), response to genomic selection per year improved up to 68.9%, 91.3%, and 92.6% compared with response to phenotypic selection per year, respectively.Subject Area: Quantitative genetics and Mendelian inheritance
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Silva, Marlon Peres da, Antônio Teixeira do Amaral Júnior, Rosana Rodrigues, Messias Gonzaga Pereira, and Alexandre Pio Viana. "Genetic control on morphoagzronomic traits in snap bean." Brazilian Archives of Biology and Technology 47, no. 6 (November 2004): 855–62. http://dx.doi.org/10.1590/s1516-89132004000600004.
Повний текст джерелаАнотація:
Five divergent snap bean accessions from the vegetables germplasm bank at UENF and their ten diallel hybrids were evaluated to inheritance on five morphoagronomic traits using Hayman's methodology (1954). The results showed that additive effects were predominant for pod weight per plant, number of seeds per pod, height of the insertion of the first pod and number of days to flowering while non-additive effects were more important for number of pods per plant. The best strategy to be adopted was the use of these acessions in an intrapopulation breeding program aiming the obtaintion of superior segregants. For pod numbers the indicated strategy would be an interpopulational breeding procedure, to exploite the heterosis related to the non-additive effects. The analysis also revealed that dominant alleles increased the number of pods per plant, pod weight per plant and number of seeds per pod. Allelic interaction was overdominance to the number of pods per plant, while the partial dominance controled the expression of other traits.
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Rettew, David C., Irene Rebollo-Mesa, James J. Hudziak, Gonneke Willemsen, and Dorret I. Boomsma. "Non-additive and Additive Genetic Effects on Extraversion in 3314 Dutch Adolescent Twins and Their Parents." Behavior Genetics 38, no. 3 (February 1, 2008): 223–33. http://dx.doi.org/10.1007/s10519-008-9192-5.
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Hunt, Colleen H., Alison B. Smith, David R. Jordan, and Brian R. Cullis. "Predicting Additive and Non-additive Genetic Effects from Trials Where Traits Are Affected by Interplot Competition." Journal of Agricultural, Biological, and Environmental Statistics 18, no. 1 (November 9, 2012): 53–63. http://dx.doi.org/10.1007/s13253-012-0117-7.
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S.C, GORAY, KHOSLA H.K, and NIGAM P.K. "ANALYSIS OF COMBINING ABILITY IN LINSEED (LINUM USITATISSIMUM L.)." Madras Agricultural Journal 77, september December (1990): 465–69. http://dx.doi.org/10.29321/maj.10.a01995.
Повний текст джерелаАнотація:
In linseed seed yield and plant height were found to be governed by additive genetic variance and remaining by non additive genetic variance. Three crosses R552 x GP440, R17 x R556 and GP194 x GP440 were promising. For reciprocal effects, cross R17 x R556 was most promising.
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Faraji-Arough, Hadi, Gholamreza Dashab, Mahmoud Ghazaghi, and Mohammad Rokouei. "Bayesian analysis of additive and non-additive genetic variances of body weight gain traits in crossbred population of Japanese quail." Spanish Journal of Agricultural Research 20, no. 2 (April 20, 2022): e0402. http://dx.doi.org/10.5424/sjar/2022202-18428.
Повний текст джерелаАнотація:
Aim of study: To select the appropriate model for body weight gain (BWG) traits in different ages and estimation of additive and non-additive genetic variances based on the best model, of a crossbred population of quail.
Area of study: Zabol, Iran
Materials and methods: Four strains of Japanese quail, including Italian Speckled, Tuxedo, Pharaoh, and A&M Texas, were used to create a crossbred population in a partial diallel design over 4 generations. BWG traits were calculated as the average growth performance of the bird in a 5-day period from hatch to 45 days of age. Analyses were performed using the Bayesian method by fitting 24 models including the additive and non-additive genetic effects. The deviance information criteria (DIC) was used for the selection of an appropriate model for each trait.
Main results: Based on DIC, the maternal genetic, maternal permanent environmental, dominance and epistasis effects had a significant contribution to the best model for BWG traits before 25 days of age, whereas these effects were not significant on BWG traits at the end of ages. With the best model, direct heritability of BWG traits in different ages ranged from 0.037 (BWG15-20) to 0.199 (BWG5-10). The maternal genetic and maternal permanent environmental as a proportion of phenotypic variance was less than 10% and 5%, respectively. The ratio of dominance and epistasis variance was in the range of 0.016-0.019, and 0.016-0.019, respectively.
Research highlights: Non- additive genetic effects are important for the early BWG traits and must be included in the evaluation models to have accurate estimates.
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Siddiqui, Abad, Babu Lal, and R. Khatri. "Genetic variability in mulberry for foliar traits." Indian Journal of Forestry 26, no. 3 (September 1, 2003): 217–19. http://dx.doi.org/10.54207/bsmps1000-2003-v2hrgm.
Повний текст джерелаАнотація:
The present study was undertaken with 7 mulberry genotypes to determine the genetic variation in foliar traits. Among the seven foliar traits studied high heritability associated with high genetic advance recorded in L x B ratio and leaf area due to additive gene effects and selection based on these traits may be effective. High estimate of heritability with low genetic advance observed for other foliar traits, viz., leaf length, leaf breadth, petiole length and moisture percentage is due to non additive gene effects and for improvement of these traits heterosis breeding might be useful.
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Svensson, Dan A., Bo Larsson, Elisabet Waldenlind, and Nancy L. Pedersen. "Genetic and Environmental Influences on Expression of Recurrent Headache as a Function of the Reporting Age in Twins." Twin Research 5, no. 4 (August 1, 2002): 277–86. http://dx.doi.org/10.1375/twin.5.4.277.
Повний текст джерелаАнотація:
AbstractTo explore age-related mechanisms in the expression of recurrent headache, we evaluated whether genetic and environmental influences are a function of the reporting age using questionnaire information that was gathered in 1973 for 15- to 47-year-old Swedish twins (n =12,606 twin pairs). Liability to mixed headache (mild migraine and tension-type headache) was explained by non-additive genetic influences (49%) in men aged from 15 to 30 years and additive genetic plus shared environmental influences (28%) in men aged from 31 to 47 years. In women, the explained proportion of variance, which was mainly due to additive genetic effects, ranged from 61% in adolescent twins to 12% in twins aged from 41 to 47 years, whereas individual specific environmental variance was significantly lower in twins aged from 15 to 20 years than in twins aged from 21 to 30 years. Liability to migrainous headache (more severe migraine) was explained by non-addi-tive genetic influences in men, 32% in young men and 45% in old men, while total phenotypic variance was significantly lower in young men than in old men. In women, the explained proportion of variance ranged from 91% in the youngest age group to 37% in the oldest age group, with major contributions from non-additive effects in young and old women (15–20 years and 41–47 years, respectively) and additive genetic effects in intermediate age groups (21–40 years). While total variance showed a positive age trend, genetic variance tended to be stable across age groups, whereas individual specific environmental variance was significantly lower in adolescent women as compared to older women.
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Oldroyd, BP, and C. Moran. "Additive and Heterotic Genetic Effects in the Haplo-diploid Honeybee Apis Mellifera." Australian Journal of Biological Sciences 40, no. 1 (1987): 57. http://dx.doi.org/10.1071/bi9870057.
Повний текст джерелаАнотація:
Nine lines of honeybees were used to form a 9 x 9 partial diallel cross. Hamuli number was determined for samples of worker offspring. One set of workers was reared in non-maternal colonies which had been made uniform, as far as possible, with respect to colony strength (number of workers), while another set was sampled directly from the combs of each maternal colony. Combining ability analysis of variance revealed significant additive and non-additive genetic effects for both sets of data, regardless of whether inbred parentals were included or excluded from the analysis. Uniform rearing removed average heterosis and reciprocal effects.
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CHAUDHARY, RAJNI, LALRENGPUII SAILO, AKANSHA SINGH, A. KARTHIKEYAN, ARNAV MEHROTRA, S. K. MONDAL, N. R. SAHOO, and AMIT KUMAR. "Genetic parameter estimates for growth performance of crossbred piglets." Indian Journal of Animal Sciences 90, no. 1 (February 18, 2020): 102–4. http://dx.doi.org/10.56093/ijans.v90i1.98237.
Повний текст джерелаАнотація:
The direct heritability estimates for piglet weights in pre and post weaning stages were moderate and improvement through mass selection is plausible. In the pre-weaning stage, the piglets had maximum genetic potential at birth (BW) to be exploited through direct selection. The 3 random effects, namely direct additive, maternal additive and litter permanent environmental effects had significant roles during different phases of pre-weaning growth and all must be included in the model used for formulating a breeding program. For post-weaning traits, the direct additive and permanent litter effects were the predominant factors governing the variability. The non-significance of postweaning maternal influence was as per expectation because the piglets moved away from maternal care after 8thweekof age.
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Lane, Sarah M., Alastair J. Wilson, and Mark Briffa. "Analysis of direct and indirect genetic effects in fighting sea anemones." Behavioral Ecology 31, no. 2 (January 10, 2020): 540–47. http://dx.doi.org/10.1093/beheco/arz217.
Повний текст джерелаАнотація:
Abstract Theoretical models of animal contests such as the Hawk-Dove game predict that variation in fighting behavior will persist due to mixed evolutionarily stable strategies (ESS) under certain conditions. However, the genetic basis for this variation is poorly understood and a mixed ESS for fighting can be interpreted in more than one way. Specifically, we do not know whether variation in aggression within a population arises from among-individual differences in fixed strategy (determined by an individual’s genotype—direct genetic effects [DGEs]), or from within-individual variation in strategy across contests. Furthermore, as suggested by developments of the original Hawk-Dove model, within-individual variation in strategy may be dependent on the phenotype and thus genotype of the opponent (indirect genetic effects—IGEs). Here we test for the effect of DGEs and IGEs during fights in the beadlet sea anemone Actinia equina. By exploiting the unusual reproductive system of sea anemones, combined with new molecular data, we investigate the role of both additive (DGE + IGE) and non-additive (DGE × IGE) genetic effects on fighting parameters, the latter of which have been hypothesized but never tested for explicitly. We find evidence for heritable variation in fighting ability and that fight duration increases with relatedness. Fighting success is influenced additively by DGEs and IGEs but we found no evidence for non-additive IGEs. These results indicate that variation in fighting behavior is driven by additive indirect genetic effects (DGE + IGE), and support a core assumption of contest theory that strategies are fixed by DGEs.
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NIELSEN, DAHLIA M., and B. S. WEIR. "A classical setting for associations between markers and loci affecting quantitative traits." Genetical Research 74, no. 3 (December 1999): 271–77. http://dx.doi.org/10.1017/s0016672399004231.
Повний текст джерелаАнотація:
We examine the relationships between a genetic marker and a locus affecting a quantitative trait by decomposing the genetic effects of the marker locus into additive and dominance effects under a classical genetic model. We discuss the structure of the associations between the marker and the trait locus, paying attention to non-random union of gametes, multiple alleles at the marker and trait loci, and non-additivity of allelic effects at the trait locus. We consider that this greater-than-usual level of generality leads to additional insights, in a way reminiscent of Cockerham's decomposition of genetic variance into five terms: three terms in addition to the usual additive and dominance terms. Using our framework, we examine several common tests of association between a marker and a trait.
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M, SHREEDHAR, VANISHREE S, KULKARNI M, and GANESH N. "Gene effects for certain Physical quality trauts and Grain yield in Rice." Madras Agricultural Journal 92, june (2005): 183–87. http://dx.doi.org/10.29321/maj.10.a00030.
Повний текст джерелаАнотація:
Genetic analysis of certain physical quality traits of grain in four selected rice crosses indicated that milling recovery in Chandan/Sambamahsuri, head rice recovery in IR-64/Rasi and length/breadth ratio in all the crosses studied were under the control of additive gene action indicating the possibility of true breeding progenies for these parameters. However, the inheritance of traits like kernel length and breadth was influenced by both additive and non -additive type gene actions. Importance of all types of epistatic interactions were found to be governing the inheritance of grain yield. Postponement of selection of desirable segregants, to advanced generations could be suggested to exploit such complex genetic makeup.
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J.A, PATEL, GUPTA Y.K, PATEL S.B, and PATEL J.N. "INHERITANCE OF SEED OIL CONTENT IN LINSEED UNDER DIFFERENT ENVIRONMENTS." Madras Agricultural Journal 86, june (1999): 225–28. http://dx.doi.org/10.29321/maj.10.a00587.
Повний текст джерелаАнотація:
In both the approaches. additive as well as non additive genetic variances were significant. However, additive genetic variance was of greater magnitude. Parents Chambal and Triveni had possessed maximum oil content along with high GCA effects over the environments. In pooled analysis about 1/3 crosses exhibited significant and positive SCA effects. The cross combination AKL 79 x Chambal depicted the highest SCA effect, however, the cross LCK 88062 x LW 28-9 had high oil content. For improvement of this trait pedigree selection method and diallel selection mating are suggested.
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Singh, Tushadri, J. P. Jaiswal, and Ashish Sheera. "Genetic Analysis of Heat Stress Tolerance in Wheat (Triticum aestivum L.) Using Line x Tester Mating Design." Journal of Scientific Research and Reports 30, no. 7 (July 12, 2024): 1013–20. http://dx.doi.org/10.9734/jsrr/2024/v30i72210.
Повний текст джерелаАнотація:
Bread wheat (Triticum aestivum L.) is a critical cereal crop, providing sustenance for over 35% of the global population. Bread wheat possesses remarkable adaptability to diverse climates and soil types. However, heat stress, exacerbated by global climate change, poses a significant threat to wheat production. Developing heat-tolerant wheat varieties is essential to ensuring food security. This study identified to identify genetic variance in heat tolerance through the Line × Tester analysis, a breeding tool that evaluates the combining ability of parental lines. The experimental material comprised 16 crosses derived from four high-yielding lines and four heat-tolerant testers. These were cultivated in Pantnagar, India, under late-sown conditions to replicate heat stress. Agronomic traits such as plant height, tiller number, grains per spike, days to maturity, and grain yield were evaluated. Analysis of variance (ANOVA) was used to estimate general combining ability (GCA) and specific combining ability (SCA), providing insights into additive and non-additive genetic variances. Results indicated significant genetic variability among genotypes, with substantial non-additive genetic components influencing most traits. Plant height, for instance, demonstrated significant GCA and SCA variances, with SCA effects being more pronounced. Similarly, traits like the number of tillers per plant and grains per spike were predominantly controlled by non-additive genetic factors. The study revealed that hybrid combinations significantly influenced growth and yield traits, underscoring the importance of both GCA and SCA in breeding programs. The significant Line × Tester interactions suggest that specific combinations of parental lines and testers are crucial for achieving superior phenotypes. This study supports the notion that both additive and non-additive genetic effects are vital for crop improvement under heat stress, providing a robust foundation for future breeding programs aimed at enhancing wheat resilience to increasing temperatures.
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Moreno-Gonzalez, J. "Genetic models to estimate additive and non-additive effects of marker-associated QTL using multiple regression techniques." Theoretical and Applied Genetics 85, no. 4 (December 1992): 435–44. http://dx.doi.org/10.1007/bf00222325.
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Huider, Floris, Yuri Milaneschi, Matthijs D. van der Zee, Eco J. C. de Geus, Quinta Helmer, Brenda W. J. H. Penninx, and Dorret I. Boomsma. "Major Depressive Disorder and Lifestyle: Correlated Genetic Effects in Extended Twin Pedigrees." Genes 12, no. 10 (September 26, 2021): 1509. http://dx.doi.org/10.3390/genes12101509.
Повний текст джерелаАнотація:
In recent years, evidence has accumulated with regard to the ubiquity of pleiotropy across the genome, and shared genetic etiology is thought to play a large role in the widespread comorbidity among psychiatric disorders and risk factors. Recent methods investigate pleiotropy by estimating genetic correlation from genome-wide association summary statistics. More comprehensive estimates can be derived from the known relatedness between genetic relatives. Analysis of extended twin pedigree data allows for the estimation of genetic correlation for additive and non-additive genetic effects, as well as a shared household effect. Here we conduct a series of bivariate genetic analyses in extended twin pedigree data on lifetime major depressive disorder (MDD) and three indicators of lifestyle, namely smoking behavior, physical inactivity, and obesity, decomposing phenotypic variance and covariance into genetic and environmental components. We analyze lifetime MDD and lifestyle data in a large multigenerational dataset of 19,496 individuals by variance component analysis in the ‘Mendel’ software. We find genetic correlations for MDD and smoking behavior (rG = 0.249), physical inactivity (rG = 0.161), body-mass index (rG = 0.081), and obesity (rG = 0.155), which were primarily driven by additive genetic effects. These outcomes provide evidence in favor of a shared genetic etiology between MDD and the lifestyle factors.
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Alam, MK, UK Nath, MAK Azad, MA Alam, and AA Khan. "Genetic analysis of some agronomic traits in groundnut (Arachis hypogaea L.)." International Journal of Agricultural Research, Innovation and Technology 3, no. 2 (February 2, 2014): 31–35. http://dx.doi.org/10.3329/ijarit.v3i2.17841.
Повний текст джерелаАнотація:
A 10×10 half diallel experiment was conducted on groundnut (Arachis hypogaea L.) to ascertain the gene action and genetic parameters of ten traits including 50% flowering, no. of pods per plant, plant height, harvest index, pod index, 100 pod weight, 100 kernel weight, pod size, diseases infection and yield per plot. The experiments were carried out in the Department of Genetics and Plant Breeding, Bangladesh Agricultural University (BAU), Mymensingh during the cropping season of 2010-2011. The estimates of gene effects indicated that significance of both additive and non-additive variance for pod size, 100 pod weight and diseases infection among the traits and presence of over dominance satisfying assumptions of diallel except dormancy. However, both the additive and non-additive gene affects together importance to control of most quantitative traits in the groundnut. The average degree of dominance (H1/D) 1/2 (H1 = dominance variance, D = additive variance) was higher than one, indicating over dominance for all the traits. The narrow-sense heritability was high for 50% flowering (38%), harvest index (35%), pod size (52%), 100 pod weight (35%) and yield per plot (41%) indicating that great genetic gain could be achieved for them. DOI: http://dx.doi.org/10.3329/ijarit.v3i2.17841 Int. J. Agril. Res. Innov. & Tech. 3 (2): 31-35, December, 2013
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Gomes, Gisely Paula, Douglas Zeffa, Gustavo Henrique Freiria, Felipe F. Furlan, Robison Alesandro de Queiroz, Lúcia SA Takahashi, and Leandro SA Gonçalves. "Diallel analysis of “dedo-de-moça” pepper seeds in relation to physiological potential." Horticultura Brasileira 38, no. 3 (September 2020): 301–5. http://dx.doi.org/10.1590/s0102-053620200310.
Повний текст джерелаАнотація:
ABSTRACT “Dedo-de-moça” (Capsicum baccatum var. pendulum) is one of the main chili peppers grown worldwide. However, studies on genetics and breeding of this species are rare, when compared to other Capsicum species, manly in relation to physiological seed quality traits. In this sense, this study aimed to evaluate the combining ability of “dedo-de-moça” chili pepper in relation to physiological seed quality traits, determine the gene effects involved in the expression of these traits, and identify promising hybrid combinations. Crosses among five parents (Hortivale, Horticeres, Brs Mari, UEL 110 and UEL 111) in a full diallel mating design, resulted in 20 F1 hybrids. Griffing’s diallel model was used to estimate general and specific combining ability (GCA and SCA, respectively) as well as the reciprocal effect (RE). Wide genetic variability was observed for all evaluated traits. Significant effects of GCA, SCA and RE were also verified for all traits, showing that additive, non-additive and cytoplasmic effects are involved in the genetic control of physiological seed quality. Non-additive effects were predominant for all traits, being UEL 111 (♂) × Hortivale (♀) and Hortivale (♂) × UEL 110 (♀) considered promising hybrids for obtaining more vigorous seeds with higher germination and greater longevity.