Journal articles on the topic 'Genetic trait'
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1
Rajon, Etienne, and Joshua B. Plotkin. "The evolution of genetic architectures underlying quantitative traits." Proceedings of the Royal Society B: Biological Sciences 280, no. 1769 (October 22, 2013): 20131552. http://dx.doi.org/10.1098/rspb.2013.1552.
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In the classic view introduced by R. A. Fisher, a quantitative trait is encoded by many loci with small, additive effects. Recent advances in quantitative trait loci mapping have begun to elucidate the genetic architectures underlying vast numbers of phenotypes across diverse taxa, producing observations that sometimes contrast with Fisher's blueprint. Despite these considerable empirical efforts to map the genetic determinants of traits, it remains poorly understood how the genetic architecture of a trait should evolve, or how it depends on the selection pressures on the trait. Here, we develop a simple, population-genetic model for the evolution of genetic architectures. Our model predicts that traits under moderate selection should be encoded by many loci with highly variable effects, whereas traits under either weak or strong selection should be encoded by relatively few loci. We compare these theoretical predictions with qualitative trends in the genetics of human traits, and with systematic data on the genetics of gene expression levels in yeast. Our analysis provides an evolutionary explanation for broad empirical patterns in the genetic basis for traits, and it introduces a single framework that unifies the diversity of observed genetic architectures, ranging from Mendelian to Fisherian.
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Börner, A., K. Neumann, and B. Kobiljski. "Wheat genetic resources – how to exploit?" Czech Journal of Genetics and Plant Breeding 47, Special Issue (October 20, 2011): S43—S48. http://dx.doi.org/10.17221/3253-cjgpb.
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It is estimated that world-wide existing germplasm collections contain about 7.5 million accessions of plant genetic resources for food and agriculture. Wheat (Triticum and Aegilops) represents the biggest group comprising 900 000 accessions. However, such a huge number of accessions is hindering a successful exploitation of the germplasm. The creation of core collections representing a wide spectrum of the genetic variation of the whole assembly may help to overcome the problem. Here we demonstrate the successful utilisation of such a core collection for the identification and molecular mapping of genes (Quantitative Trait Loci) determining the agronomic traits flowering time and grain yield, exploiting a marker-trait-association based technique. Significant marker-trait associations were obtained and are presented. The intrachromosomal location of many of these associations coincided with those of already identified major genes or quantitative trait loci, but others were detected in regions where no known genes have been located to date.
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Teixeira, B. B., R. R. Mota, R. B. Lôbo, L. P. Silva, A. P. Souza Carneiro, F. G. Silva, G. C. Caetano, and F. F. Silva. "Genetic evaluation of growth traits in Nellore cattle through multi-trait and random regression models." Czech Journal of Animal Science 63, No. 6 (May 25, 2018): 212–21. http://dx.doi.org/10.17221/21/2017-cjas.
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We aimed to evaluate different orders of fixed and random effects in random regression models (RRM) based on Legendre orthogonal polynomials as well as to verify the feasibility of these models to describe growth curves in Nellore cattle. The proposed RRM were also compared to multi-trait models (MTM). Variance components and genetic parameters estimates were performed via REML for all models. Twelve RRM were compared through Akaike (AIC) and Bayesian (BIC) information criteria. The model of order three for the fixed curve and four for all random effects (direct genetic, maternal genetic, permanent environment, and maternal permanent environment) fits best. Estimates of direct genetic, maternal genetic, maternal permanent environment, permanent environment, phenotypic and residual variances were similar between MTM and RRM. Heritability estimates were higher via RRM. We presented perspectives for the use of RRM for genetic evaluation of growth traits in Brazilian Nellore cattle. In general, moderate heritability estimates were obtained for the majority of studied traits when using RRM. Additionally, the precision of these estimates was higher when using RRM instead of MTM. However, concerns about the variance components estimates in advanced ages via Legendre polynomial must be taken into account in future studies.
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Skelly, Daniel A., Narayanan Raghupathy, Raymond F. Robledo, Joel H. Graber, and Elissa J. Chesler. "Reference Trait Analysis Reveals Correlations Between Gene Expression and Quantitative Traits in Disjoint Samples." Genetics 212, no. 3 (May 21, 2019): 919–29. http://dx.doi.org/10.1534/genetics.118.301865.
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Systems genetic analysis of complex traits involves the integrated analysis of genetic, genomic, and disease-related measures. However, these data are often collected separately across multiple study populations, rendering direct correlation of molecular features to complex traits impossible. Recent transcriptome-wide association studies (TWAS) have harnessed gene expression quantitative trait loci (eQTL) to associate unmeasured gene expression with a complex trait in genotyped individuals, but this approach relies primarily on strong eQTL. We propose a simple and powerful alternative strategy for correlating independently obtained sets of complex traits and molecular features. In contrast to TWAS, our approach gains precision by correlating complex traits through a common set of continuous phenotypes instead of genetic predictors, and can identify transcript–trait correlations for which the regulation is not genetic. In our approach, a set of multiple quantitative “reference” traits is measured across all individuals, while measures of the complex trait of interest and transcriptional profiles are obtained in disjoint subsamples. A conventional multivariate statistical method, canonical correlation analysis, is used to relate the reference traits and traits of interest to identify gene expression correlates. We evaluate power and sample size requirements of this methodology, as well as performance relative to other methods, via extensive simulation and analysis of a behavioral genetics experiment in 258 Diversity Outbred mice involving two independent sets of anxiety-related behaviors and hippocampal gene expression. After splitting the data set and hiding one set of anxiety-related traits in half the samples, we identified transcripts correlated with the hidden traits using the other set of anxiety-related traits and exploiting the highest canonical correlation (R = 0.69) between the trait data sets. We demonstrate that this approach outperforms TWAS in identifying associated transcripts. Together, these results demonstrate the validity, reliability, and power of reference trait analysis for identifying relations between complex traits and their molecular substrates.
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Jiang, C., and Z. B. Zeng. "Multiple trait analysis of genetic mapping for quantitative trait loci." Genetics 140, no. 3 (July 1, 1995): 1111–27. http://dx.doi.org/10.1093/genetics/140.3.1111.
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Abstract We present in this paper models and statistical methods for performing multiple trait analysis on mapping quantitative trait loci (QTL) based on the composite interval mapping method. By taking into account the correlated structure of multiple traits, this joint analysis has several advantages, compared with separate analyses, for mapping QTL, including the expected improvement on the statistical power of the test for QTL and on the precision of parameter estimation. Also this joint analysis provides formal procedures to test a number of biologically interesting hypotheses concerning the nature of genetic correlations between different traits. Among the testing procedures considered are those for joint mapping, pleiotropy, QTL by environment interaction, and pleiotropy vs. close linkage. The test of pleiotropy (one pleiotropic QTL at a genome position) vs. close linkage (multiple nearby nonpleiotropic QTL) can have important implications for our understanding of the nature of genetic correlations between different traits in certain regions of a genome and also for practical applications in animal and plant breeding because one of the major goals in breeding is to break unfavorable linkage. Results of extensive simulation studies are presented to illustrate various properties of the analyses.
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Alves, Rodrigo, João Rocha, Larissa Teodoro, Luiz Carvalho, Francisco Farias, Marcos Resende, Leonardo Bhering, and Paulo Teodoro. "Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length." Revista de la Facultad de Ciencias Agrarias UNCuyo 53, no. 1 (July 7, 2021): 1–10. http://dx.doi.org/10.48162/rev.39.001.
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Multi-trait best linear unbiased prediction (BLUP) is, generally, the most appropriate method to genetic evaluation because it considers the genetic and residual correlations among traits and conduct to higher selection accuracy. Thus, the present study aimed to identify traits correlated to the fiber length via path analysis under multi-trait BLUP for the cotton breeding. To this end, thirty-six elite lines were evaluated in three environments and phenotyped for many traits related to fiber quality and agronomic traits. Variance components were estimated via residual maximum likelihood (REML). The genetic correlation coefficients among traits were obtained through mixed model output, and to graphically express these results a correlation network was built. Subsequently, we performed path analysis considering fiber length as a principal dependent variable. Genetic parameters obtained by multi-trait BLUP model indicate that the phenotypic variance for most traits is mostly composed of residual effects, which reinforces the need for using more accurate statistical methods such as multi-trait BLUP. The results found for genetic correlations and path analysis under multi-trait BLUP reveal the difficulty of selection based on important fiber quality traits, especially fiber length, since most traits show very low cause-and-effect relationship, and other important traits present undesirable cause-and-effect relationship.
Highlights
Multiple-trait BLUP is the most appropriate method to predict genetic values.
This is the first study in cotton to perform path analysis under multiple-trait BLUP.
The findings of this study indicate that there is no genotype presenting all desirable traits.
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Yang, Chin Jian, Luis Fernando Samayoa, Peter J. Bradbury, Bode A. Olukolu, Wei Xue, Alessandra M. York, Michael R. Tuholski, et al. "The genetic architecture of teosinte catalyzed and constrained maize domestication." Proceedings of the National Academy of Sciences 116, no. 12 (March 6, 2019): 5643–52. http://dx.doi.org/10.1073/pnas.1820997116.
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The process of evolution under domestication has been studied using phylogenetics, population genetics–genomics, quantitative trait locus (QTL) mapping, gene expression assays, and archaeology. Here, we apply an evolutionary quantitative genetic approach to understand the constraints imposed by the genetic architecture of trait variation in teosinte, the wild ancestor of maize, and the consequences of domestication on genetic architecture. Using modern teosinte and maize landrace populations as proxies for the ancestor and domesticate, respectively, we estimated heritabilities, additive and dominance genetic variances, genetic-by-environment variances, genetic correlations, and genetic covariances for 18 domestication-related traits using realized genomic relationships estimated from genome-wide markers. We found a reduction in heritabilities across most traits, and the reduction is stronger in reproductive traits (size and numbers of grains and ears) than vegetative traits. We observed larger depletion in additive genetic variance than dominance genetic variance. Selection intensities during domestication were weak for all traits, with reproductive traits showing the highest values. For 17 of 18 traits, neutral divergence is rejected, suggesting they were targets of selection during domestication. Yield (total grain weight) per plant is the sole trait that selection does not appear to have improved in maize relative to teosinte. From a multivariate evolution perspective, we identified a strong, nonneutral divergence between teosinte and maize landrace genetic variance–covariance matrices (G-matrices). While the structure of G-matrix in teosinte posed considerable genetic constraint on early domestication, the maize landrace G-matrix indicates that the degree of constraint is more unfavorable for further evolution along the same trajectory.
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Snowder, G. D., and N. M. Fogarty. "Composite trait selection to improve reproduction and ewe productivity: a review." Animal Production Science 49, no. 1 (2009): 9. http://dx.doi.org/10.1071/ea08184.
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Reproduction and ewe productivity are complex composite traits that are influenced by several component traits. Genetic improvement by selection for an individual component trait may not always be advantageous because adverse or neutral genetic relationships can exist among the component traits. Selection for an overall composite trait of ewe productivity, defined as litter weight weaned per ewe joined, can result in a balanced biological composite trait with favourable responses in component traits including fertility, number of lambs born, lamb survival, lactation and lamb growth. Selection for litter weight weaned may also overcome adverse genetic relationships among reproductive component traits. This review examines the genetic responses of selecting directly for litter weight weaned, compared with selection responses for one or more of its component traits. It is concluded that selection to improve reproductive efficiency and ewe productivity, under most production and environmental systems, would benefit from selection for a composite trait such as litter weight weaned, rather than for a single component trait.
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Khan, M. S., K. Z. Gondal, S. H. Raza, and A. A. Asghar. "First Lactation Genetic Parameters of Buffaloes Under Multiple Trait Animal Model." Journal of Agricultural and Marine Sciences [JAMS] 2 (January 1, 1997): 27. http://dx.doi.org/10.24200/jams.vol2iss0pp27-30.
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There are many computational algorithms available for estimating (co) variance components under multiple trait models. Paternal half-sib correlation is the most commonly used method for estimating genetic parameters of economic traits of buffaloes. The models used are Single trait, ignoring covariances with other traits. The relationship matrices are also ignored. This study was undertaken to estimate genetic parameters of first lactation traits of Nili Ravi buffaloes under a multiple trait animal model. First lactation milk yield was l7% heritable when traits such as age of calving interval were considered. Age at first calving was 18% heritable with very low genetic correlations with other traits. Lactation length, dry period and calving interval were lowly heritable traits. Estimates differed by inclusion or exclusion of traits due to the covariances present among all these traits. A high genetic correlation between mills yield and lactation length (0.74) does not warrant the selection of milk yield as the only trait.
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Howe, Glenn T., Sally N. Aitken, David B. Neale, Kathleen D. Jermstad, Nicholas C. Wheeler, and Tony HH Chen. "From genotype to phenotype: unraveling the complexities of cold adaptation in forest trees." Canadian Journal of Botany 81, no. 12 (December 1, 2003): 1247–66. http://dx.doi.org/10.1139/b03-141.
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Adaptation to winter cold in temperate and boreal trees involves complex genetic, physiological, and developmental processes. Genecological studies demonstrate the existence of steep genetic clines for cold adaptation traits in relation to environmental (mostly temperature related) gradients. Population differentiation is generally stronger for cold adaptation traits than for other quantitative traits and allozymes. Therefore, these traits appear to be under strong natural selection. Nonetheless, high levels of genetic variation persist within populations. The genetic control of cold adaptation traits ranges from weak to strong, with phenological traits having the highest heritabilities. Within-population genetic correlations among traits range from negligible to moderate. Generally, bud phenology and cold hardiness in the fall are genetically uncorrelated with bud phenology and cold hardiness in the spring. Analyses of quantitative trait loci indicate that cold adaptation traits are mostly controlled by multiple genes with small effects and that quantitative trait loci × environment interactions are common. Given this inherent complexity, we suggest that future research should focus on identifying and developing markers for cold adaptation candidate genes, then using multilocus, multi allelic analytical techniques to uncover the relationships between genotype and phenotype at both the individual and population levels. Ultimately, these methods may be useful for predicting the performance of genotypes in breeding programs and for better understanding the evolutionary ecology of forest trees.Key words: association genetics, cold hardiness, dormancy, genecology, bud phenology, quantitative trait loci.
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Zhou, Yan, Aaron Kusmec, Seyed Vahid Mirnezami, Lakshmi Attigala, Srikant Srinivasan, Talukder Z. Jubery, James C. Schnable, Maria G. Salas-Fernandez, Baskar Ganapathysubramanian, and Patrick S. Schnable. "Identification and utilization of genetic determinants of trait measurement errors in image-based, high-throughput phenotyping." Plant Cell 33, no. 8 (May 20, 2021): 2562–82. http://dx.doi.org/10.1093/plcell/koab134.
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Abstract The accuracy of trait measurements greatly affects the quality of genetic analyses. During automated phenotyping, trait measurement errors, i.e. differences between automatically extracted trait values and ground truth, are often treated as random effects that can be controlled by increasing population sizes and/or replication number. In contrast, there is some evidence that trait measurement errors may be partially under genetic control. Consistent with this hypothesis, we observed substantial nonrandom, genetic contributions to trait measurement errors for five maize (Zea mays) tassel traits collected using an image-based phenotyping platform. The phenotyping accuracy varied according to whether a tassel exhibited “open” versus. “closed” branching architecture, which is itself under genetic control. Trait-associated SNPs (TASs) identified via genome-wide association studies (GWASs) conducted on five tassel traits that had been phenotyped both manually (i.e. ground truth) and via feature extraction from images exhibit little overlap. Furthermore, identification of TASs from GWASs conducted on the differences between the two values indicated that a fraction of measurement error is under genetic control. Similar results were obtained in a sorghum (Sorghum bicolor) plant height dataset, demonstrating that trait measurement error is genetically determined in multiple species and traits. Trait measurement bias cannot be controlled by increasing population size and/or replication number.
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Lozada, Dennis, and Arron Carter. "Insights into the Genetic Architecture of Phenotypic Stability Traits in Winter Wheat." Agronomy 10, no. 3 (March 7, 2020): 368. http://dx.doi.org/10.3390/agronomy10030368.
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Examining the architecture of traits through genomics is necessary to gain a better understanding of the genetic loci affecting important traits to facilitate improvement. Genomewide association study (GWAS) and genomic selection (GS) were implemented for grain yield, heading date, and plant height to gain insights into the genetic complexity of phenotypic stability of traits in a diverse population of US Pacific Northwest winter wheat. Analysis of variance using the Additive Main Effect and Multiplicative Interaction (AMMI) approach revealed significant genotype and genotype by environment interactions. GWAS identified 12 SNP markers distributed across 10 chromosomes affecting variation for both trait and phenotypic stability, indicating potential pleiotropic effects and signifying that similar genetic loci could be associated with different aspects of stability. The lack of stable and major effect loci affecting phenotypic variation supports the complexity of stability of traits. Accuracy of GS was low to moderate, between 0.14 and 0.66, indicating that phenotypic stability is under genetic control. The moderate to high correlation between trait and trait stability suggests the potential of simultaneous selection for trait and trait stability. Our results demonstrate the complex genetic architecture of trait stability and show the potential for improving stability in winter wheat using genomic-assisted approaches.
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Hernández, Mariano Agustín, Juan Adolfo López, and Eduardo Pablo Cappa. "Improving Genetic Analysis of Corymbia citriodora subsp. variegata with Single- and Multiple-Trait Spatial-Competition Models." Forest Science 65, no. 5 (August 30, 2019): 570–80. http://dx.doi.org/10.1093/forsci/fxz020.
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Abstract Environmental heterogeneity and/or genetic and environmental competition were quantified on two growth traits, diameter at breast height and total height, and wood density in a progeny trial of Corymbia citriodora subsp. variegata. Three single-trait mixed models with random spatial and/or competition effects were compared to a standard analysis by analyzing fit, dispersion parameters, accuracy of breeding values, genetic gains, and ranking of trees. In addition, a multiple-trait spatial-competition model was fitted to estimate correlations among direct and indirect additive genetic effects, and to explore relations between traits. Single-trait analyses with spatial and/or competition effects outperformed the standard model. However, the performance of these models depended on the sensitivity of each trait to detect each effect. Direct–indirect genetic correlations from the multiple-trait spatial-competition model showed inverse and strong relations among growth traits and wood density, suggesting that growth traits can be affected by competition and environmental heterogeneity, but also wood density might be influenced by these effects. The approach proposed was useful to improve the genetic analysis of the species as well as to gain an understanding of the genetic relations between traits under the influence of environmental heterogeneity and competition.
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Lopez, Bryan Irvine, Ju-Hwan Son, Kangseok Seo, and Dajeong Lim. "Estimation of Genetic Parameters for Reproductive Traits in Hanwoo (Korean Cattle)." Animals 9, no. 10 (September 24, 2019): 715. http://dx.doi.org/10.3390/ani9100715.
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Genetic parameters for the reproductive traits of Hanwoo cattle were estimated using data obtained from 15,355 cows in 92 herds across South Korea, which were inseminated from May 1997 to July 2016. An “average information” restricted maximum likelihood (REML) procedure that fit in single-trait and multi-trait animal models was used to estimate the variance components of age at first calving (AFC), calving interval (CI), days open (DO), and gestation length (GL). Results showed the low estimates of heritability for all reproductive traits from both single-trait and multi-trait models. Estimates of heritability for AFC were 0.08 and 0.10 with single-trait and multi-trait models, respectively, while the estimates of heritability using the same animal models ranged from 0.01 to 0.07, 0.01 to 0.09, and 0.10 to 0.16 for CI, DO, and GL, accordingly. While AFC showed positive genetic correlations of 0.52 and 0.46 with CI and DO, respectively, the estimates of genetic and phenotypic correlations of GL with AFC were close to zero. Moreover, phenotypic correlations of GL with CI and DO were also close to zero; however, the corresponding genetic correlations were 0.13 and –0.38 for CI and DO, respectively. These estimated variance components and genetic correlations for reproductive traits can be utilized for genetic improvement programs of Hanwoo cattle.
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Kruijer, Willem, Pariya Behrouzi, Daniela Bustos-Korts, María Xosé Rodríguez-Álvarez, Seyed Mahdi Mahmoudi, Brian Yandell, Ernst Wit, and Fred A. van Eeuwijk. "Reconstruction of Networks with Direct and Indirect Genetic Effects." Genetics 214, no. 4 (February 3, 2020): 781–807. http://dx.doi.org/10.1534/genetics.119.302949.
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Genetic variance of a phenotypic trait can originate from direct genetic effects, or from indirect effects, i.e., through genetic effects on other traits, affecting the trait of interest. This distinction is often of great importance, for example, when trying to improve crop yield and simultaneously control plant height. As suggested by Sewall Wright, assessing contributions of direct and indirect effects requires knowledge of (1) the presence or absence of direct genetic effects on each trait, and (2) the functional relationships between the traits. Because experimental validation of such relationships is often unfeasible, it is increasingly common to reconstruct them using causal inference methods. However, most current methods require all genetic variance to be explained by a small number of quantitative trait loci (QTL) with fixed effects. Only a few authors have considered the “missing heritability” case, where contributions of many undetectable QTL are modeled with random effects. Usually, these are treated as nuisance terms that need to be eliminated by taking residuals from a multi-trait mixed model (MTM). But fitting such an MTM is challenging, and it is impossible to infer the presence of direct genetic effects. Here, we propose an alternative strategy, where genetic effects are formally included in the graph. This has important advantages: (1) genetic effects can be directly incorporated in causal inference, implemented via our PCgen algorithm, which can analyze many more traits; and (2) we can test the existence of direct genetic effects, and improve the orientation of edges between traits. Finally, we show that reconstruction is much more accurate if individual plant or plot data are used, instead of genotypic means. We have implemented the PCgen-algorithm in the R-package pcgen.
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Edwards, M. D., C. W. Stuber, and J. F. Wendel. "Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action." Genetics 116, no. 1 (May 1, 1987): 113–25. http://dx.doi.org/10.1093/genetics/116.1.113.
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ABSTRACT Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17–20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800–1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.
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Zavadilová, Ludmila, Eva Kašná, Zuzana Krupová, and Michaela Brzáková. "Genetic parameters for clinical mastitis in Czech Holstein cattle." Czech Journal of Animal Science 65, No. 12 (December 21, 2020): 463–72. http://dx.doi.org/10.17221/151/2020-cjas.
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Genetic parameters were estimated for clinical mastitis in Czech Holstein cattle. The datasets included 14 329 cows with 28 626 lactations. Clinical mastitis was defined as 0/1 occurrence per lactation. Single- or multi-trait repeatability linear animal models were employed for estimation of (co)variances and prediction of conventional or genomic breeding values. The inclusion of the random herd-year-month effect in the model was analysed. The estimated heritability for clinical mastitis ranged from 2.10% to 2.72%, while permanent environmental variance ratios or random herd-year-month effect ratios were twice higher than heritability. In the multi-trait models, udder type traits, such as fore udder attachment, rear udder attachment, rear udder width, front teat placement and udder depth, were employed. The highest genetic correlations of clinical mastitis occurred with rear udder width (0.41) and the lowest with front teat placement (–0.10). Both the multi-trait model and the genomic model provided breeding value estimates with higher reliability. In contrast, the model with random herd-year-season effects provided breeding values with lower accuracy.
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Keim, P., B. W. Diers, T. C. Olson, and R. C. Shoemaker. "RFLP mapping in soybean: association between marker loci and variation in quantitative traits." Genetics 126, no. 3 (November 1, 1990): 735–42. http://dx.doi.org/10.1093/genetics/126.3.735.
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Abstract We have constructed a genetic map for soybean and identified associations between genetic markers and quantitative trait loci. One-hundred-fifty restriction fragment length polymorphisms (RFLPs) were used to identify genetic linkages in an F2 segregating population from an interspecific cross (Glycine max x Glycine soja). Twenty-six genetic linkage groups containing ca. 1200 recombination units are reported. Progeny-testing of F2-derived families allowed quantitative traits to be evaluated in replicated field trials. Genomic regions, which accounted for a portion of the genetic variation (R2 = 16 to 24%) in several reproductive and morphological traits, were linked to RFLP markers. Significant associations between RFLP markers and quantitative trait loci were detected for eight of nine traits evaluated. The ability to identify genes within a continuously varying trait has important consequences for plant breeding and for understanding evolutionary processes.
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Winterbottom, Robyn. "Predisposition to Impulsivity and Risk-taking: Dopamine D4 Receptor (DRD4) Polymorphic Gene Linked to “Novelty Seeking” Personality Trait." Revue interdisciplinaire des sciences de la santé - Interdisciplinary Journal of Health Sciences 1, no. 1 (February 10, 2010): 79. http://dx.doi.org/10.18192/riss-ijhs.v1i1.1539.
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Genetic variation may play a significant role in the expression of complex personality and psychological traits. This article examines the relationship between heritable biological mechanisms and the psychological trait, impulsivity. In particular, dopamine is proposed to play a role in impulsive behaviours, and numerous studies have implicated functional polymorphisms of dopamine-related genes in impulsivity. This article reviews several studies concerning the role of dopamine receptor (DRD4) polymorphisms in the expression of an impulsivity sub-trait known as “novelty seeking”. Furthermore, this article focuses on recent approaches to the study of genetic variation, approaches to the measurement of novelty seeking, as well as other possible regulators of the trait in addition to genetics.
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Rodrigues, Francelino Neiva, José Lindenberg Rocha Sarmento, Tânia Maria Leal, Adriana Mello de Araújo, and Luiz Antonio Silva Figueiredo Filho. "Genetic parameters for worm resistance in Santa Inês sheep using the Bayesian animal model." Animal Bioscience 34, no. 2 (February 1, 2021): 185–91. http://dx.doi.org/10.5713/ajas.19.0634.
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Objective: The objective of this study was to estimate the genetic parameters for worm resistance (WR) and associated characteristics, using the linear-threshold animal model via Bayesian inference in single- and multiple-trait analyses.Methods: Data were collected from a herd of Santa Inês breed sheep. All information was collected with animals submitted to natural contamination conditions. All data (number of eggs per gram of feces [FEC], Famacha score [FS], body condition score [BCS], and hematocrit [HCT]) were collected on the same day. The animals were weighed individually on the day after collection (after 12-h fasting). The WR trait was defined by the multivariate cluster analysis, using the FEC, HCT, BCS, and FS of material collected from naturally infected sheep of the Santa Inês breed. The variance components and genetic parameters for the WR, FEC, HCT, BCS, and FS traits were estimated using the Bayesian inference under the linear and threshold animal model.Results: A low magnitude was obtained for repeatability of worm-related traits. The mean values estimated for heritability were of low-to-high (0.05 to 0.88) magnitude. The FEC, HCT, BCS, FS, and body weight traits showed higher heritability (although low magnitude) in the multiple-trait model due to increased information about traits. All WR characters showed a significant genetic correlation, and heritability estimates ranged from low (0.44; single-trait model) to high (0.88; multiple-trait model).Conclusion: Therefore, we suggest that FS be included as a criterion of ovine genetic selection for endoparasite resistance using the trait defined by multivariate cluster analysis, as it will provide greater genetic gains when compared to any single trait. In addition, its measurement is easy and inexpensive, exhibiting greater heritability and repeatability and a high genetic correlation with the trait of resistance to worms.
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Huisman, A. E., D. J. Brown, A. J. Ball, and H. U. Graser. "Genetic parameters for bodyweight, wool, and disease resistance and reproduction traits in Merino sheep. 1. Description of traits, model comparison, variance components and their ratios." Australian Journal of Experimental Agriculture 48, no. 9 (2008): 1177. http://dx.doi.org/10.1071/ea08119.
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Both wool and sheep meat industries are interested in sheep that have a high reproduction performance and are resistant to internal parasites, in addition to the traditional traits. There is considerable interest in breeding sheep for wool, carcass, reproductive and internal parasite resistance traits simultaneously. The objective of this study was to estimate single trait genetic parameters for 40 traits recorded in Merino sheep, covering bodyweight, carcass, wool, reproduction and internal parasite resistance traits. This also involved determining the appropriate models. The results from this study will be used to review the genetic parameters used in the routine genetic evaluations conducted by Sheep Genetics. The most appropriate models included a maternal genetic effect and covariance between direct and maternal genetic effects for most of the bodyweight traits, greasy and clean fleece weight, fibre diameter and coefficient of variation of fibre diameter. The permanent environment due to the dam was not included for any trait. There was considerable genetic variation in most traits analysed; lowest heritabilities (0.09–0.10) were found for number of lambs born and weaned per lambing opportunity, and highest heritabilities (0.62–0.77) for fibre diameter. The estimated heritabilities and genetic variances, in combination with the estimated correlations, indicate that there is potential to make genetic improvement in most traits currently recorded in Australian Merino sheep.
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Carvalho, N. S., D. S. Daltro, J. D. Machado, E. V. Camargo, J. C. C. Panetto, and J. A. Cobuci. "Genetic parameters and genetic trends of conformation and management traits in Dairy Gir cattle." Arquivo Brasileiro de Medicina Veterinária e Zootecnia 73, no. 4 (August 2021): 938–48. http://dx.doi.org/10.1590/1678-4162-12341.
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ABSTRACT The objective of this study was to estimate genetic parameters and genetic trends of different conformation and management traits regularly measured within the context of the National Dairy Gir Breeding Program (PNMGL). The estimation of genetic and residual variances for each trait was performed using average information restricted maximum likelihood (AI-REML) procedure in AIREMLF90 program software. The population was divided into three subpopulations constituted by measured females (with phenotype records), all females, and males. Linear regressions were applied for each trait, considering two periods of birth (1st period: 1938-1996; 2nd period: 1997-2012). The estimated heritability of conformation and management traits varied from 0.01 to 0.53, denoting a perspective of genetic improvement through selection and corrective matings for purebred Dairy Gir populations. The average genetic changes in conformation and management traits were, in general, variable and inexpressive, showing that the selection of Dairy Gir may have had been directed essentially to increase milk yield. The analysis of the two periods of birth indicated that some linear traits present progress (although inexpressive) in the 2nd period (more recent period).
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Li, Yuling, Yongbin Dong, Suzhun Niu, and Dangqun Cui. "The genetic relationship among plant-height traits found using multiple-trait QTL mapping of a dent corn and popcorn cross." Genome 50, no. 4 (April 2007): 357–64. http://dx.doi.org/10.1139/g07-018.
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Plant height (PH) is one of the most important traits in maize breeding programs. In popcorn, inferior plant traits can be improved with the dent/flint corn germplasm. In the current study, a total of 259 F2:3 families, developed from a cross between a dent corn inbred and a popcorn inbred, were evaluated for 4 PH traits. Quantitative trait loci (QTLs) for each trait were detected using composite interval mapping methods. In addition, genetic interrelationships were investigated using multiple-trait joint analysis for PH with ear height (EH), and for PH with top height (TH). In total, 6, 5, 2, and 6 QTLs were identified for PH, EH, TH, and TH/PH in single-trait analysis, respectively. Joint-analysis data suggest a strong and complex genetic relationship between PH and EH, and between PH and EH, with no QTLs controlling any single trait independently. In addition, 4 kinds of QTLs detected were classified as closely linked QTLs, pleiotropic QTLs, QTLs with opposite effects, and additional QTLs. It was, consequently, difficult to improve lodge resistance through selection on any individual PH trait. The current study demonstrates that multiple-trait joint analysis not only identified additional QTLs, but also revealed the genetic relationship among different highly correlated traits at the molecular level.
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Guo, Bin, and Baolin Wu. "Integrate multiple traits to detect novel trait–gene association using GWAS summary data with an adaptive test approach." Bioinformatics 35, no. 13 (November 23, 2018): 2251–57. http://dx.doi.org/10.1093/bioinformatics/bty961.
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Abstract Motivation Genetics hold great promise to precision medicine by tailoring treatment to the individual patient based on their genetic profiles. Toward this goal, many large-scale genome-wide association studies (GWAS) have been performed in the last decade to identify genetic variants associated with various traits and diseases. They have successfully identified tens of thousands of disease-related variants. However they have explained only a small proportion of the overall trait heritability for most traits and are of very limited clinical use. This is partly owing to the small effect sizes of most genetic variants, and the common practice of testing association between one trait and one genetic variant at a time in most GWAS, even when multiple related traits are often measured for each individual. Increasing evidence suggests that many genetic variants can influence multiple traits simultaneously, and we can gain more power by testing association of multiple traits simultaneously. It is appealing to develop novel multi-trait association test methods that need only GWAS summary data, since it is generally very hard to access the individual-level GWAS phenotype and genotype data. Results Many existing GWAS summary data-based association test methods have relied on ad hoc approach or crude Monte Carlo approximation. In this article, we develop rigorous statistical methods for efficient and powerful multi-trait association test. We develop robust and efficient methods to accurately estimate the marginal trait correlation matrix using only GWAS summary data. We construct the principal component (PC)-based association test from the summary statistics. PC-based test has optimal power when the underlying multi-trait signal can be captured by the first PC, and otherwise it will have suboptimal performance. We develop an adaptive test by optimally weighting the PC-based test and the omnibus chi-square test to achieve robust performance under various scenarios. We develop efficient numerical algorithms to compute the analytical P-values for all the proposed tests without the need of Monte Carlo sampling. We illustrate the utility of proposed methods through application to the GWAS meta-analysis summary data for multiple lipids and glycemic traits. We identify multiple novel loci that were missed by individual trait-based association test. Availability and implementation All the proposed methods are implemented in an R package available at http://www.github.com/baolinwu/MTAR. The developed R programs are extremely efficient: it takes less than 2 min to compute the list of genome-wide significant single nucleotide polymorphisms (SNPs) for all proposed multi-trait tests for the lipids GWAS summary data with 2.5 million SNPs on a single Linux desktop. Supplementary information Supplementary data are available at Bioinformatics online.
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Harpak, Arbel, and Molly Przeworski. "The evolution of group differences in changing environments." PLOS Biology 19, no. 1 (January 25, 2021): e3001072. http://dx.doi.org/10.1371/journal.pbio.3001072.
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The selection pressures that have shaped the evolution of complex traits in humans remain largely unknown, and in some contexts highly contentious, perhaps above all where they concern mean trait differences among groups. To date, the discussion has focused on whether such group differences have any genetic basis, and if so, whether they are without fitness consequences and arose via random genetic drift, or whether they were driven by selection for different trait optima in different environments. Here, we highlight a plausible alternative: that many complex traits evolve under stabilizing selection in the face of shifting environmental effects. Under this scenario, there will be rapid evolution at the loci that contribute to trait variation, even when the trait optimum remains the same. These considerations underscore the strong assumptions about environmental effects that are required in ascribing trait differences among groups to genetic differences.
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Burke, John M., Shunxue Tang, Steven J. Knapp, and Loren H. Rieseberg. "Genetic Analysis of Sunflower Domestication." Genetics 161, no. 3 (July 1, 2002): 1257–67. http://dx.doi.org/10.1093/genetics/161.3.1257.
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Abstract Quantitative trait loci (QTL) controlling phenotypic differences between cultivated sunflower and its wild progenitor were investigated in an F3 mapping population. Composite interval mapping revealed the presence of 78 QTL affecting the 18 quantitative traits of interest, with 2–10 QTL per trait. Each QTL explained 3.0–68.0% of the phenotypic variance, although only 4 (corresponding to 3 of 18 traits) had effects >25%. Overall, 51 of the 78 QTL produced phenotypic effects in the expected direction, and for 13 of 18 traits the majority of QTL had the expected effect. Despite being distributed across 15 of the 17 linkage groups, there was a substantial amount of clustering among QTL controlling different traits. In several cases, regions influencing multiple traits harbored QTL with antagonistic effects, producing a cultivar-like phenotype for some traits and a wild-like phenotype for others. On the basis of the directionality of QTL, strong directional selection for increased achene size appears to have played a central role in sunflower domestication. None of the other traits show similar evidence of selection. The occurrence of numerous wild alleles with cultivar-like effects, combined with the lack of major QTL, suggests that sunflower was readily domesticated.
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Falk, Kevin G., Talukder Zaki Jubery, Jamie A. O’Rourke, Arti Singh, Soumik Sarkar, Baskar Ganapathysubramanian, and Asheesh K. Singh. "Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters." Plant Phenomics 2020 (June 9, 2020): 1–23. http://dx.doi.org/10.34133/2020/1925495.
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We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications=14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.
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Wolf, J., E. Žáková, and E. Groeneveld. "Genetic parameters for a joint genetic evaluation of production and reproduction traits in pigs." Czech Journal of Animal Science 50, No. 3 (December 6, 2011): 96–103. http://dx.doi.org/10.17221/4001-cjas.
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The covariance structure was estimated by REML for a joint genetic evaluation of production and reproduction traits for Czech Landrace (58 258 records) and Czech Large White (167 161 records) pigs using four-trait animal models. The following traits were analysed: lean mean percentage at the end of the performance test in the field, estimated from ultrasonic measurements unadjusted for live weight (LM), average daily gain in field test (in g/day) calculated as weight at the end of the test divided by age at the end of the test (ADG), number of piglets born alive in parity 1 (NBA1) and number of piglets born alive in parity 2 and subsequent parities (NBA2+). The heritabilities were in the range from 0.30 to 0.37 for LM, from 0.13 to 0.18 for ADG, from 0.09 to 0.13 for NBA1 and from 0.10 to 0.14 for NBA2+, depending on the breed and on the model (herd-year-season random or fixed). Genetic correlations between production and reproduction traits were estimated to be non-zero. Correlations between traits caused by the herd-year-season effect were mostly positive. As a general conclusion, the joint genetic evaluation of production and reproduction traits is recommended. The herd-year-season effect should be preferably considered as random.
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Ma, Xiang, Ole F. Christensen, Hongding Gao, Ruihua Huang, Bjarne Nielsen, Per Madsen, Just Jensen, et al. "Prediction of breeding values for group-recorded traits including genomic information and an individually recorded correlated trait." Heredity 126, no. 1 (July 14, 2020): 206–17. http://dx.doi.org/10.1038/s41437-020-0339-3.
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AbstractRecords on groups of individuals could be valuable for predicting breeding values when a trait is difficult or costly to measure on single individuals, such as feed intake and egg production. Adding genomic information has shown improvement in the accuracy of genetic evaluation of quantitative traits with individual records. Here, we investigated the value of genomic information for traits with group records. Besides, we investigated the improvement in accuracy of genetic evaluation for group-recorded traits when including information on a correlated trait with individual records. The study was based on a simulated pig population, including three scenarios of group structure and size. The results showed that both the genomic information and a correlated trait increased the accuracy of estimated breeding values (EBVs) for traits with group records. The accuracies of EBV obtained from group records with a size 24 were much lower than those with a size 12. Random assignment of animals to pens led to lower accuracy due to the weaker relationship between individuals within each group. It suggests that group records are valuable for genetic evaluation of a trait that is difficult to record on individuals, and the accuracy of genetic evaluation can be considerably increased using genomic information. Moreover, the genetic evaluation for a trait with group records can be greatly improved using a bivariate model, including correlated traits that are recorded individually. For efficient use of group records in genetic evaluation, relatively small group size and close relationships between individuals within one group are recommended.
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Petrides, K. V., Philip A. Vernon, Julie Aitken Schermer, and Livia Veselka. "Trait Emotional Intelligence and the Dark Triad Traits of Personality." Twin Research and Human Genetics 14, no. 1 (February 1, 2011): 35–41. http://dx.doi.org/10.1375/twin.14.1.35.
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This study presents the first behavioral genetic investigation of the relationships between trait emotional intelligence (trait EI or trait emotional self-efficacy) and the Dark Triad traits of narcissism, Machiavellianism, and psychopathy. In line with trait EI theory, the construct correlated positively with narcissism, but negatively with the other two traits. Generally, the correlations were consistent across the 4 factors and 15 facets of the construct. Cholesky decomposition analysis revealed that the phenotypic associations were primarily due to correlated genetic factors and secondarily due to correlated nonshared environmental factors, with shared environmental factors being nonsignificant in all cases. Results are discussed from the perspective of trait EI theory with particular reference to the issue of adaptive value.
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Storz, Jay F., Jamie T. Bridgham, Scott A. Kelly, and Theodore Garland. "Genetic approaches in comparative and evolutionary physiology." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 309, no. 3 (August 1, 2015): R197—R214. http://dx.doi.org/10.1152/ajpregu.00100.2015.
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Whole animal physiological performance is highly polygenic and highly plastic, and the same is generally true for the many subordinate traits that underlie performance capacities. Quantitative genetics, therefore, provides an appropriate framework for the analysis of physiological phenotypes and can be used to infer the microevolutionary processes that have shaped patterns of trait variation within and among species. In cases where specific genes are known to contribute to variation in physiological traits, analyses of intraspecific polymorphism and interspecific divergence can reveal molecular mechanisms of functional evolution and can provide insights into the possible adaptive significance of observed sequence changes. In this review, we explain how the tools and theory of quantitative genetics, population genetics, and molecular evolution can inform our understanding of mechanism and process in physiological evolution. For example, lab-based studies of polygenic inheritance can be integrated with field-based studies of trait variation and survivorship to measure selection in the wild, thereby providing direct insights into the adaptive significance of physiological variation. Analyses of quantitative genetic variation in selection experiments can be used to probe interrelationships among traits and the genetic basis of physiological trade-offs and constraints. We review approaches for characterizing the genetic architecture of physiological traits, including linkage mapping and association mapping, and systems approaches for dissecting intermediary steps in the chain of causation between genotype and phenotype. We also discuss the promise and limitations of population genomic approaches for inferring adaptation at specific loci. We end by highlighting the role of organismal physiology in the functional synthesis of evolutionary biology.
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Torres-Ruiz, José M., Antoine Kremer, Madeline R. Carins Murphy, Tim Brodribb, Laurent J. Lamarque, Laura Truffaut, Fabrice Bonne, Alexis Ducousso, and Sylvain Delzon. "Genetic differentiation in functional traits among European sessile oak populations." Tree Physiology 39, no. 10 (October 1, 2019): 1736–49. http://dx.doi.org/10.1093/treephys/tpz090.
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Abstract The vulnerability of forest species and tree populations to climate change is related to the exposure of the ecosystem to extreme climatic conditions and to the adaptive capacity of the population to cope with those conditions. Adaptive capacity is a relatively under-researched topic within the forest science community, and there is an urgent need to understand to what extent particular combinations of traits have been shaped by natural selection under climatic gradients, potentially resulting in adaptive multi-trait associations. Thus, our aim was to quantify genetic variation in several leaf and woody traits that may contribute to multi-trait associations in which intra-specific variation could represent a source for species adaptation to climate change. A multi-trait approach was performed using nine Quercus petraea provenances originating from different locations that cover most of the species’ distribution range over Europe and that were grown in a common garden. Multiple adaptive differences were observed between oak provenances but also some evolutionary stasis. In addition, our results revealed higher genetic differentiation in traits related to phenology and growth than in those related to xylem anatomy, physiology and hydraulics, for which no genetic differentiation was observed. The multiple associations between those traits and climate variables resulting from multivariate and path analyses suggest a multi-trait association largely involving phenological and growth traits for Q. petraea.
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Malmberg, Russell L., Willie L. Rogers, and Magdy S. Alabady. "A carnivorous plant genetic map: pitcher/insect-capture QTL on a genetic linkage map ofSarracenia." Life Science Alliance 1, no. 6 (November 29, 2018): e201800146. http://dx.doi.org/10.26508/lsa.201800146.
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The study of carnivorous plants can afford insight into their unique evolutionary adaptations and their interactions with prokaryotic and eukaryotic species. ForSarracenia(pitcher plants), we identified 64 quantitative trait loci (QTL) for insect-capture traits of the pitchers, providing the genetic basis for differences between the pitfall and lobster-trap strategies of insect capture. The linkage map developed here is based upon the F2 of a cross betweenSarracenia roseaandSarracenia psittacina; we mapped 437 single nucleotide polymorphism and simple sequence repeat markers. We measured pitcher traits which differ betweenS. roseaandS. psittacina, mapping 64 QTL for 17 pitcher traits; there are hot-spot locations where multiple QTL map near each other. There are epistatic interactions in many cases where there are multiple loci for a trait. The QTL map uncovered the genetic basis for the differences between pitfall- and lobster-traps, and the changes that occurred during the divergence of these species. The longevity and clonability ofSarraceniaplants make the F2 mapping population a resource for mapping more traits and for phenotype-to-genotype studies.
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Houle, D. "Comparing evolvability and variability of quantitative traits." Genetics 130, no. 1 (January 1, 1992): 195–204. http://dx.doi.org/10.1093/genetics/130.1.195.
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Abstract There are two distinct reasons for making comparisons of genetic variation for quantitative characters. The first is to compare evolvabilities, or ability to respond to selection, and the second is to make inferences about the forces that maintain genetic variability. Measures of variation that are standardized by the trait mean, such as the additive genetic coefficient of variation, are appropriate for both purposes. Variation has usually been compared as narrow sense heritabilities, but this is almost always an inappropriate comparative measure of evolvability and variability. Coefficients of variation were calculated from 842 estimates of trait means, variances and heritabilities in the literature. Traits closely related to fitness have higher additive genetic and nongenetic variability by the coefficient of variation criterion than characters under weak selection. This is the reverse of the accepted conclusion based on comparisons of heritability. The low heritability of fitness components is best explained by their high residual variation. The high additive genetic and residual variability of fitness traits might be explained by the great number of genetic and environmental events they are affected by, or by a lack of stabilizing selection to reduce their phenotypic variance. Over one-third of the quantitative genetics papers reviewed did not report trait means or variances. Researchers should always report these statistics, so that measures of variation appropriate to a variety of situations may be calculated.
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Moreira, Heverton Luis, Marcos Eli Buzanskas, Danisio Prado Munari, Érika Breda Canova, Raysildo Barbosa Lôbo, and Claudia Cristina Paro de Paz. "REPRODUCTIVE TRAITS SELECTION IN NELORE BEEF CATTLE." Ciência e Agrotecnologia 39, no. 4 (August 2015): 355–62. http://dx.doi.org/10.1590/s1413-70542015000400006.
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Genetic breeding programs of beef cattle in Brazil are including new features, mainly related to reproductive efficiency.Thus, it is necessary to study the effectiveness of selection and quantify genetic gain for these traits in herds. This study estimated genetic and phenotypic parameters and genetic trends for reproductive traits used in breeding programs for Nelore beef cattle. The traits studied were the scrotal circumference (SC) at 365 and 450 days of age (SC365 and SC450), age at first calving (AFC) and gestation length, as a cow trait (GLcow) and a calf trait (GLcalf). The (co)variance components were obtained with the Restricted Maximum Likelihood Methodology in a single and double-trait analysis of the animal model. For scrotal circumference (SC365 and SC450), positive and favorable genetic gains were observed. For AFC, GLcow and GLcalf, the trends were favorable for selection, but without significant genetic gain. Selection for large SC may reduce AFC and improve female reproductive efficiency. The selection for reproductive traits (SC365, SC450, AFC and GL) may improve reproductive and productive efficiency of Nelore cattle, if used as a selection criterion.
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Xiao, Jinhua, Jiming Li, Silvana Grandillo, Sang Nag Ahn, Longping Yuan, Steven D. Tanksley, and Susan R. McCouch. "Identification of Trait-Improving Quantitative Trait Loci Alleles From a Wild Rice Relative, Oryza rufipogon." Genetics 150, no. 2 (October 1, 1998): 899–909. http://dx.doi.org/10.1093/genetics/150.2.899.
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Abstract Wild species are valued as a unique source of genetic variation, but they have rarely been used for the genetic improvement of quantitative traits. To identify trait-improving quantitative trait loci (QTL) alleles from exotic species, an accession of Oryza rufipogon, a relative of cultivated rice, was chosen on the basis of a genetic diversity study. An interspecific BC2 testcross population (V20A/O. rufipogon//V20B///V20B////Ce64) consisting of 300 families was evaluated for 12 agronomically important quantitative traits. The O. rufipogon accession was phenotypically inferior for all 12 traits. However, transgressive segregants that outperformed the original elite hybrid variety, V20A/Ce64, were observed for all traits examined. A set of 122 RFLP and microsatellite markers was used to identify QTL. A total of 68 significant QTL were identified, and of these, 35 (51%) had beneficial alleles derived from the phenotypically inferior O. rufipogon parent. Nineteen (54%) of these beneficial QTL alleles were free of deleterious effects on other characters. O. rufipogon alleles at two QTL on chromosomes 1 and 2 were associated with an 18 and 17% increase in grain yield per plant, respectively, without delaying maturity or increasing plant height. This discovery suggests that the innovative use of molecular maps and markers can alter the way geneticists utilize wild and exotic germplasm.
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Novotný, L., J. Frelich, J. Beran, and L. Zavadilová. "Genetic relationship between type traits, number of lactations initiated, and lifetime milk performance in Czech Fleckvieh cattle." Czech Journal of Animal Science 62, No. 12 (November 2, 2017): 501–10. http://dx.doi.org/10.17221/60/2017-cjas.
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Genetic relationship was analyzed between type traits and longevity measures in dual-purpose cattle. Data from 91 486 Czech Fleckvieh cows first calved between 2003 and 2009 were used. Longevity was defined as the actual number of lactations initiated per cow and also as functional longevity, which incorporated an adjustment to account for variation in voluntary culling based upon milk production. Lifetime performance was defined as cumulative milk production through the 6<sup>th</sup> parity. All cows were scored for conformation traits during their first lactation. Genetic correlations between these traits and longevity measures were estimated by bivariate analysis using the DMU variance component program package. Type trait heritabilities ranged from 0.30 to 0.59, while heritabilities for longevity and functional longevity were 0.06 and 0.05, respectively. Heritability of lifetime performance was 0.08. Genetic correlations between type traits and longevity measures ranged from low to intermediate values. Genetic correlations of the measured body size traits to the real and functional longevity ranged from –0.06 to –0.29, for udder traits from –0.02 to 0.33, and for foot and leg traits from –0.03 to 0.17. Genetic correlations between the measured body size traits and lifetime performance ranged from –0.03 to –0.30, for udder traits from 0.05 to 0.47, for foot and leg traits from –0.07 to 0.15. Genetic correlations of composite trait scores for frame, muscularity, feet and legs, and udder with longevity traits ranged from –0.20 to 0.41 and for lifetime performance –0.14 to 0.51. The highest genetic correlations between a type trait and functional longevity were for composite udder score (0.25), feet and legs (0.26), and udder depth (0.33), suggesting that these traits could serve as indicators of functional longevity. We conclude that selection based upon easily and inexpensively measured type traits could improve functional longevity of cows as well as lifetime milk production.
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Weller, J. I., M. Soller, and T. Brody. "Linkage analysis of quantitative traits in an interspecific cross of tomato (lycopersicon esculentum x lycopersicon pimpinellifolium) by means of genetic markers." Genetics 118, no. 2 (February 1, 1988): 329–39. http://dx.doi.org/10.1093/genetics/118.2.329.
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Abstract Linkage relationships between loci affecting quantitative traits (QTL) and marker loci were examined in an interspecific cross between Lycopersicon esculentum and Lycopersicon pimpinellifolium. Parental lines differed for six morphological markers and for four electrophoretic markers. Almost 1700 F-2 plants were scored with respect to the genetic markers and also with respect to 18 quantitative traits. Major genes affecting the quantitative traits were not found, but out of 180 possible marker x trait combinations, 85 showed significant quantitative effects associated with the genetic markers. The average marker-associated main effect was on the order of 6% of the mean value of the trait. Most of the main effects were apparently due to linkage of QTL to the marker loci rather than to pleiotropy. Fourteen of the traits showed at least one highly significant effect of opposite sign to the overall difference between the parental lines, demonstrating the ability of this design to uncover cryptic genetic variation. Significant variance and skewness effects on the quantitative traits were found to be associated with the genetic markers, suggesting the possible presence of loci affecting the variance and shape of quantitative trait distribution in a population. Most marker-associated quantitative effects showed some degree of dominance, generally in the direction of the L. pimpinellifolium parent. When the significant marker-associated effects were examined in pairs, 12% showed significant interaction effects. The results of this study illustrate the potential usefulness of this type of analysis for the detailed genetic investigation of quantitative trait variation in suitably marked populations.
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Brown, D. J., R. M. Jones, and G. N. Hinch. "Genetic parameters for lamb autopsy traits." Animal Production Science 54, no. 6 (2014): 736. http://dx.doi.org/10.1071/an13227.
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Heritabilities and genetic correlations were estimated between individual and composite autopsy traits for lambs autopsied in the Australian Sheep Cooperative Research Centre information nucleus flocks between 2008 and 2011 (n = 3224). Correlations were also estimated between autopsy categories and the production parameters Yearling greasy-fleece weight and Yearling weight, and the potential survival indicator traits: Lamb ease, Thorax circumference and Crown–rump length. All autopsy trait heritability estimates were low (range 0.01–0.04). For all traits, a higher proportion of the variance was partitioned into the maternal permanent environment than the direct effects (range 0.01–0.12), suggesting that selection based on lamb autopsy results would impart little advantage over the lamb survival trait itself in improving lamb survival. Genetic correlations between Lamb ease and all autopsy traits were positive, indicating that birth trauma is related to all causes of lamb deaths and that Lamb ease may be a useful selection criterion in seedstock flocks to reduce overall mortality. There were also positive genetic correlations between Thorax circumference after adjusting for birthweight and two classes of dystocia, as well as a positive correlation between Thorax circumference and incidences of Starvation mismothering, implying that Thorax circumference may be a useful indirect field measurement to reduce death from these causes. Of concern were the antagonistic genetic correlations estimated between Yearling greasy-fleece weight and a composite trait of All Dystocia classes plus Starvation mismothering (0.27 ± 0.15), implying that selection for increased fleece weight could be having a detrimental effect on overall lamb survival.
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Stalder, Kenneth J. "296 Awardee Talk: The Genetics of Sow Longevity." Journal of Animal Science 98, Supplement_4 (November 3, 2020): 28. http://dx.doi.org/10.1093/jas/skaa278.050.
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Abstract Sow longevity is a key productivity indicator trait that has real economic and welfare importance for commercial swine farms globally. The average parity at culling is 3.8 parities. Reports indicate that it takes 3 to 4 parities before a sow “pays for herself.” Research groups around the world have reported heritabilities estimates for sow longevity traits ranging from 0.05 to 0.35. Estimate differences result from the animal population under evaluation, the trait being evaluated, and the methodology employed to obtain the genetic parameter estimate. Because sow longevity is measured at the end of the sow’s productive life, indicator traits like age at first farrowing, leg conformation, and other traits are utilized in gilt selection programs. The genetic correlations between sow longevity and lifetime production traits range have been reported to range from 0.64 to 0.94, suggesting that selection will improve sow longevity. Genetic markers have been identified that affect both sow longevity and other indicator traits. Selection to improved sow longevity still requires phenotypes. Future technologies, e.g. CT scans, digital images, and automated disease detection, will provide additional phenotypes. Continued hardware, software, and molecular developments will improve selection accuracy for sow longevity traits and related traits. Research is needed to evaluate the impact that non-additive genetic effects have on sow longevity and other fitness-related traits. Sow longevity seems to be an ideal trait to employ genomic selection in order to make more rapid trait improvements because it is measured late in life, it is sex-limited, and the trait is not directly measured on nucleus animals. In conclusion, sow longevity and related traits have sufficient heritability and variation to improve through traditional and genomic enhanced selection methods. Selection programs employing effective genomic selection programs will be more effective in improving sow longevity trait and related traits and ultimately economical return.
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Li, H., T. Guillemaud, B. W. French, U. Kuhlmann, and S. Toepfer. "Phenotypic trait changes in laboratory – reared colonies of the maize herbivore, Diabrotica virgifera virgifera." Bulletin of Entomological Research 104, no. 1 (November 22, 2013): 97–115. http://dx.doi.org/10.1017/s000748531300059x.
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AbstractThe North American and European maize pest Diabrotica virgifera virgifera LeConte (Coleoptera: Chrysomelidae) was used to assess whether conditions of the natal field, subsequent laboratory rearing, or genetic population origin affect phenotypic traits of fitness, activity, or morphometrics. Standardized laboratory bioassays with large sample sizes revealed that none of the 16 tested traits, except crawling behaviours, appeared consistently stable across all seven tested colonies. Environmental conditions in the natal field of the F0 generation affected trait averages of the subsequently reared F1 generation in laboratory in ca. 47% of cases, and trait variability in 67% of cases. This was apparent for fitness and morphometrics, but less obvious for activity traits. Early generation laboratory rearing affected trait averages in ca. 56% of cases: morphometrics changed; fecundity and egg survival increased from F1 to F2. Trait variability increased or decreased in 38% of cases. Laboratory rearing for over more than 190 generations affected the trait averages in 60% of cases, reflected by decreases in flight activity and increases in body size, weight, and fecundity to some extent. It had little effect on trait variability, especially so for morphometric variability. The genetic population origin affected average levels of 55% and variability of 63% of phenotypic traits. A comparison among D. v. virgifera studies might be difficult if they use different populations or laboratory colonies. It is advised to consider possible effects of original field conditions, laboratory rearing, and population genetics when planning comparative studies targeting fitness, activity, or morphometric questions regarding Diabrotica species.
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Sun, Wei, Shinsheng Yuan, and Ker-Chau Li. "Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study." BMC Genomics 9, no. 1 (2008): 242. http://dx.doi.org/10.1186/1471-2164-9-242.
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Merk, Heather L., Shawn C. Yarnes, Allen Van Deynze, Nankui Tong, Naama Menda, Lukas A. Mueller, Martha A. Mutschler, Steven A. Loewen, James R. Myers, and David M. Francis. "Trait Diversity and Potential for Selection Indices Based on Variation Among Regionally Adapted Processing Tomato Germplasm." Journal of the American Society for Horticultural Science 137, no. 6 (November 2012): 427–37. http://dx.doi.org/10.21273/jashs.137.6.427.
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For many horticultural crops, selection is based on quality as well as yield. To investigate the distribution of trait variation and identify those attributes appropriate for developing selection indices, we collected and organized information related to fruit size, shape, color, soluble solids, acid, and yield traits for 143 processing tomato (Solanum lycopersicum L.) lines from North America. Evaluation of the germplasm panel was conducted in a multiyear, multilocation trial. Data were stored in a flat-file format and in a trait ontology database, providing a public archive. We estimated variance components and proportion of variance resulting from genetics for each trait. Genetic variance was low to moderate (range, 0.03–0.51) for most traits, indicating high environmental influence on trait expression and/or complex genetic architecture. Phenotypic values for each line were estimated across environments as best linear unbiased predictors (BLUPs). Principal components (PC) analysis using the trait BLUPs provided a means to assess which traits explained variation in the germplasm. The first two PCs explained 28.0% and 16.2% of the variance and were heavily weighted by measures of fruit shape and size. The third PC explained 12.9% of the phenotypic variance and was determined by fruit color and yield components. Trait BLUPs and the first three PCs were also used to explore the relationship between phenotypes and the origin of the accessions. We were able to differentiate germplasm for fruit size, fruit shape, yield, soluble solids, and color based on origin, indicating regional breeding programs provide a source of trait variation. These analyses suggest that multitrait selection indices could be established that encompass quality traits in addition to yield. However, such indices will need to balance trait correlations and be consistent with market valuation.
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Toral, Fábio Luiz Buranelo, and Maurício Mello de Alencar. "Alternatives for analysis of performance data and ranking of Charolais x Nellore crossbred bulls in performance tests." Revista Brasileira de Zootecnia 39, no. 7 (July 2010): 1483–90. http://dx.doi.org/10.1590/s1516-35982010000700013.
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It was evaluated alternatives for analysis of performance records and ranking of Charolais x Zebu crossbred bulls. Data of weight at six ages and average daily weight gain in eight periods of 883 21/32 Charolais + 11/32 Nellore bulls in performance tests were used. The direct additive genetic values were predicted in single trait analysis using animal models with classificatory fixed effects of contemporary groups and age of dam at calving and age of animal at weighing as linear covariable, depending on the trait. As random effects, it was considered the direct additive genetic effect, the permanent maternal environmental and residual effects for all traits. Phenotypic values adjusted for fixed effects included in the model of each trait were also obtained. The Spearman correlation between predicted direct additive genetic values and adjusted phenotypic values ranged from 0.43 to 0.95, depending on the trait and year of birth of the animals. The accuracies of genetic values increased according to the number of animals with utilized data and they were always higher to those estimated for the adjusted phenotypic values. The magnitude of change in ranking the bulls depends on the considered trait. The estimates of correlations of predicted genetic values with the real genetic values of the analyzed traits of growth are higher than those among the adjusted phenotypic values and the real genetic values.
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Fuerst-Waltl, Birgit, Birgit Lang, and Christian Fuerst. "Economic values for a total merit index of dairy goats in Austria." Die Bodenkultur: Journal of Land Management, Food and Environment 69, no. 2 (October 5, 2018): 97–104. http://dx.doi.org/10.2478/boku-2018-0009.
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SummaryWhen defining a total merit index, all economically important traits, both performance and functional traits shall be considered. Aside from breeding values, their reliabilities and all genetic relationships, the knowledge of the economic importance of all traits involved is required. In this study, economic values were derived for the most numerous dairy goat breed in Austria, the Saanen goat. Calculated marginal utilities are expressed per average ewe place and year. The calculations were based on a herd model including dairy production, rearing and fattening of goat kids. Economic values are calculated by multiplying the marginal utilities with the genetic standard deviations of the traits. The economic value is thus defined by the value of one unit of genetic superiority of a trait. In order to derive the economic value of one trait, a single parameter in the model was varied while keeping all other traits constant. The relative economic values (in %) for the trait complexes were as follows: dairy : functional : meat traits = 74 : 25 : 1, respectively. Within the dairy complex, milk carrier yield was the most important trait, while in the functional traits fertility, defined as conception rate, had the highest economic weight.
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Gjessing, Håkon K., and Rolv Terje Lie. "Biometrical modelling in genetics: are complex traits too complex?" Statistical Methods in Medical Research 17, no. 1 (February 2008): 75–96. http://dx.doi.org/10.1177/0962280207081241.
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The field of traditional biometrical genetics uses mixed-effects models to quantify the influence of genetic and environmental factors on a biological trait, based essentially on estimating within-family trait correlations. Such analyses provide a useful preview of what may be discovered with the emerging full-scale genotyping strategies. However, biometrical analyses require unrealistically large sample sizes to obtain a reasonable precision, particularly for dichotomous traits. In addition, it may be very difficult to separate genetic and environmental effects because environmental correlations are poorly understood. We illustrate these and other difficulties using population-based cousins and nuclear family data for birth weight, collected from the Medical Birth Registry of Norway.
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Donoghue, K. A., S. J. Lee, P. F. Parnell, and W. S. Pitchford. "Maternal body composition in seedstock herds. 4. Genetic parameters for body composition of Angus and Hereford cows." Animal Production Science 58, no. 1 (2018): 145. http://dx.doi.org/10.1071/an13258.
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The genetics of body composition traits measured before calving and at weaning in the first and second parities were evaluated in 5975 Angus and 1785 Hereford cows. Traits measured were liveweight, body condition score and hip height and ultrasound scanned measurements of subcutaneous P8 and 12/13th rib fat depth, loin eye muscle area and intramuscular fat percentage. Corresponding yearling measures on these animals were obtained for analyses of relationships between yearling information with later-in-life traits. There was moderate genetic variation in all body composition traits measured at pre-calving and weaning in Angus (h2 = 0.14–0.59) and Hereford (h2 = 0.14–0.64) cows. Genetic correlations between measurements of the same trait at pre-calving and weaning were consistently positive and high in both parities for both breeds, indicating animals were ranking similarly for the same trait measured over time. Genetic correlations between measurements of different traits were generally consistent over time (pre-calving and weaning) in both breeds, indicating genetic relationships between traits were not changing significantly over time. Genetic correlations with corresponding yearling measures of body composition were consistently positive and high for the first parity, and lower for the second parity. The results of this study indicate that genetic improvement in body composition traits in cows is possible, and that body composition information recorded at yearling age is a reasonably good predictor of later in life performance for these traits.
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Dugand, Robert J., J. David Aguirre, Emma Hine, Mark W. Blows, and Katrina McGuigan. "The contribution of mutation and selection to multivariate quantitative genetic variance in an outbred population of Drosophila serrata." Proceedings of the National Academy of Sciences 118, no. 31 (July 29, 2021): e2026217118. http://dx.doi.org/10.1073/pnas.2026217118.
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Genetic variance is not equal for all multivariate combinations of traits. This inequality, in which some combinations of traits have abundant genetic variation while others have very little, biases the rate and direction of multivariate phenotypic evolution. However, we still understand little about what causes genetic variance to differ among trait combinations. Here, we investigate the relative roles of mutation and selection in determining the genetic variance of multivariate phenotypes. We accumulated mutations in an outbred population of Drosophila serrata and analyzed wing shape and size traits for over 35,000 flies to simultaneously estimate the additive genetic and additive mutational (co)variances. This experimental design allowed us to gain insight into the phenotypic effects of mutation as they arise and come under selection in naturally outbred populations. Multivariate phenotypes associated with more (less) genetic variance were also associated with more (less) mutational variance, suggesting that differences in mutational input contribute to differences in genetic variance. However, mutational correlations between traits were stronger than genetic correlations, and most mutational variance was associated with only one multivariate trait combination, while genetic variance was relatively more equal across multivariate traits. Therefore, selection is implicated in breaking down trait covariance and resulting in a different pattern of genetic variance among multivariate combinations of traits than that predicted by mutation and drift. Overall, while low mutational input might slow evolution of some multivariate phenotypes, stabilizing selection appears to reduce the strength of evolutionary bias introduced by pleiotropic mutation.
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Ali, A., K. Javed, I. Zahoor, and K. M. Anjum. "Analysis of non-genetic and genetic influences underlying the growth of Kajli lambs." South African Journal of Animal Science 50, no. 4 (October 29, 2020): 613–25. http://dx.doi.org/10.4314/sajas.v50i4.13.
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Data on 2931 Kajli lambs, born from 2007 to 2018, were used to quantify environmental and genetic effects on growth performance of Kajli sheep. Traits considered for evaluation were birth weight (BWT), 120-day adjusted weight (120DWT), 180-day adjusted weight (180DWT), 270-day adjusted weight (270DWT), and 365-day adjusted weight (365DWT). Fixed effects of year of birth, season of birth, sex, birth type, and dam age on these traits were evaluated using linear procedures of SAS, 9.1. Similarly, BWT, 120DWT, 180DWT, and 270DWT were used as fixed effects mixed model analyses. Variance components, heritability and breeding values were estimated by restricted maximum likelihood. The genetic trend for each trait was obtained by regression of the estimated breeding values (EBV) on year of birth. Analyses revealed substantial influence of birth year on all traits. Sex and birth type were the significant sources of variation for BWT and 120DWT. Season of birth did not influence birth weight meaningfully, but had a significant role in the expression of 120DWT, 180DWT, and 270DWT. Heritability estimates were generally low (0.003 ± 0.018 to 0.099 ± 0.067) for all traits. With the exception of the genetic correlation of 180DWT and 365DWT, the genetic correlations between trait were strong and positive. Only 365DWT had a positive genetic trend. Although the heritability estimates for almost all weight traits were low, high and positive genetic correlations between BWT and other weight traits suggest that selection based on BWT would result in the improvement of other weight traits as a correlated response.Keywords: bodyweight, breeding value, genetic correlation, sheep
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Rosa, J. O., G. C. Venturini, T. C. S. Chud, B. C. Pires, M. E. Buzanskas, N. B. Stafuzza, G. R. Furquim, et al. "Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens." Czech Journal of Animal Science 63, No. 6 (May 25, 2018): 230–36. http://dx.doi.org/10.17221/116/2017-cjas.
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This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.