Relevant bibliographies by topics / Genetic trait

Academic literature on the topic 'Genetic trait'

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Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Genetic trait"

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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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Dissertations / Theses on the topic "Genetic trait"

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Salmon, Anderson Tricia. "Sickle Cell Trait and Genetic Counseling." ScholarWorks, 2017. https://scholarworks.waldenu.edu/dissertations/4020.

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Sickle cell trait (SCT) is a very prevalent disorder in the United States, especially among African Americans or people of African descent. However, even with the prevalence of the disorder, there are no standardized guidelines for providing patients with information about SCT and the implications of the disorder at physicals and well-check visits. The purpose of this evidence-based project was to increase awareness for African American patients 18-44 years old in the practice setting about SCT and to provide options for testing and genetic counseling. Kotter's contemporary change theory was used as a guide to implement the new practice approach. A quasi-experimental, single-group, pretest-posttest-only design was used to explore the relationship between providing consistent SCT education and the impact on the rate of SCT screening and genetic counseling. A total of 71 patients participated in the program. The analysis showed a significant (p < 0.001) mean difference of 18.16 points from the preintervention SCT and genetics test mean, which indicated that the intervention was successful in raising SCT and genetics knowledge scores among the target population. The results demonstrated that the implementation of SCT education in the practice setting can enhance social implications related to SCT awareness and opportunities for SCT testing and genetic counseling. The implementation of SCT clinical guidelines can help to increase awareness about SCT and improve the overall population health and reduce the financial burden affiliated with care of those with sickle cell disease and SCT complications.
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Finucane, Hilary Kiyo. "Functional and cross-trait genetic architecture of common diseases and complex traits." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112906.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2017
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 201-245).
In this thesis, I introduce new methods for learning about diseases and traits from genetic data. First, I introduce a method for partitioning heritability by functional annotation from genome-wide association summary statistics, and I apply it to 17 diseases and traits and many different functional annotations. Next, I show how to apply this method to use gene expression data to identify diseaserelevant tissues and cell types. I next introduce a method for estimating genetic correlation from genome-wide association summary statistics and apply it to estimate genetic correlations between all pairs of 24 diseases and traits. Finally, I consider a model of disease subtypes and I show how to determine a lower bound on the sample size required to distinguish between two disease subtypes as a function of several parameters.
by Hilary Kiyo Finucane.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Mathematics
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Lu, Yue. "Genetic mapping of quantitative trait loci for slow-rusting traits in wheat." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/32179.

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Doctor of Philosophy
Department of Agronomy
Guihua Bai
Allan K. Fritz
Wheat leaf rust, caused by Puccinia triticina, is an important fungal disease worldwide. Growing resistant cultivars is an effective practice to reduce the losses caused by the disease, and using slow-rusting resistance genes can improve the durability of rust resistance in the cultivars. CI13227 is a winter wheat line that shows a high level of slow-rusting resistance to leaf rust and has been studied extensively. In this research, two recombinant inbreed line (RIL) populations derived from CI13227 x Suwon (104 RILs) and CI13227 x Everest (184 RILs) and one doubled haploid (DH) population derived from CI13227 x Lakin with 181 lines were used to identify quantitative trait loci (QTLs) for slow leaf rusting resistance. Each population and its parents were evaluated for slow-rusting traits in two greenhouse experiments. A selected set of 384 simple sequence repeat markers (SSRs), single nucleotide polymorphism markers (SNPs) derived from genotyping-by-sequencing (GBS-SNPs) or 90K-SNP chip (90K-SNPs) were analyzed in the three populations. Six QTLs for slow-rusting resistance, QLr.hwwgru-2DS, QLr.hwwgru-7BL, QLr.hwwgru-7AL, QLr.hwwgru-3B_1, QLr.hwwgru-3B_2, and QLr.hwwgru-1D were detected in the three populations with three stable QTLs, QLr.hwwgru-2DS, QLr.hwwgru-7BL and QLr.hwwgru-7AL. These were detected and validated by Kompetitive Allele-Specific PCR (KASP) markers converted from GBS-SNPs and 90K-SNPs in at least two populations. Another three QTLs were detected only in a single population, and either showed a minor effect or came from the susceptible parents. The KASP markers tightly linked to QLr.hwwgru-2DS (IWB34642, IWB8545 and GBS_snpj2228), QLr.hwwgru-7BL (GBS_snp1637 and IWB24039) and QLr.hwwgru-7AL (IWB73053 and IWB42182) are ready to be used in marker-assisted selection (MAS) to transfer these QTLs into wheat varieties to improve slow-rusting resistance in wheat.
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Porter, Heather Frances. "Multi-trait methods for genetic association testing." Thesis, King's College London (University of London), 2018. https://kclpure.kcl.ac.uk/portal/en/theses/multitrait-methods-for-genetic-association-testing(d040066c-8b0f-4f1b-bd0c-7be3f144b7e2).html.

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The early stages of the genome-wide association study (GWAS) era were dominated by studies focusing on single phenotypes, while in recent years there has been growing interest in multi-trait GWAS. A wide variety of multi-trait GWAS methods have been developed, but publications introducing new methods are highly inconsistent in their evaluation of method performance, obscuring their relative merit. Facilitated by burgeoning national biobank resources, multi-trait analyses are set to become more routinely applied, making understanding their relative performance increasingly important. We develop a simulation framework to model the complex networks underlying multivariate genetic epidemiology. We exploit our simulation framework to perform a comprehensive comparison study of the leading multi-trait GWAS methods, providing a web application and open-source software program implementing our simulation framework for further benchmarking of multi-trait GWAS methods. Motivated by our comparison results, we develop novel methodology and present a series of multi-trait analyses. We perform multi-trait genome-wide analyses on publicly available GWAS summary statistics on 19 traits – metabolic, anthropometric and psychiatric. We develop and apply two summary statistic methods: one that has increased power to detect pleiotropic effects on multiple traits, and one that is more powerful for detecting heterogeneous genetic effects. Polygenic risk scores (PRS) are now a commonly used tool for performing phenotype prediction from genetics, assessing the genetic aetiology underlying diseases, and testing for shared genetic aetiology among traits. Using UK Biobank data, we explore the predictive ability of PRS computed across multiple traits for Major Depressive Disorder (MDD). The MDD PRS itself has so far offered modest prediction of MDD case/control status; we explore the use of PRS built on traits correlated with MDD to improve predictive ability. We build main effect and interaction models, using both AIC and BIC stepwise variable selection, and cross-validation, to establish the most predictive models.
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Schaeffer, George Barry. "Genetic evaluation of a linear trait description." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/101262.

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Data for this study were 79,997 evaluations for 12 individual body and udder traits of Holstein cows. Type scores were subjectively assigned by trained personnel of Select Sires, Inc., Plain City, OH, through their corrective mating and young sire evaluation programs. After editing data to remove incomplete, erroneous and duplicate records, 56,642 records were used to calculate overall and regional age adjustment factors. Genetic parameters were estimated. Heritabilities ranged from .40 for stature to .14 for fore udder. Standard errors ranged from .039 for stature to .018 for fore udder. Genetic correlations ranged from +.75 between teats and udder support to -.61 between feet and legs. Phenotypic correlations were generally smaller than genetic correlations, ranging from .56 between udder support and teats to -.23 for dairyness and strength. These findings were in general agreement with previous research. Genetic evaluations for the 12 individual linear traits were made using Herdmate Comparison (HC) and Best Linear Unbiased Prediction (BLUP) methods. Mean evaluations by HC were near zero, and ranged from .026 for stature to -.027 for teats. Mean repeatability also showed very little variation, ranging from .404 for stature to .241 for teats. BLUP evaluations were similar to HC evaluations, with mean evaluation ranging from .121 for feet to -.183 for dairyness. Direct correlations between BLUP and HC evaluations ranged from .90 for stature to .74 for dairyness. Forty-eight different combinations of minimum daughter numbers and model variables were tested to predict sires' overall evaluations for type from linear trait evaluations using regression analysis. Results indicate that with 5 or more daughters per sire, all predictions tested were similar in accuracy for Predicted Difference for Type.
M.S.
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Forsberg, Simon. "Complex Trait Genetics : Beyond Additivity." Doctoral thesis, Uppsala universitet, Institutionen för medicinsk biokemi och mikrobiologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-307837.

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The link between the genotype and the phenotype of an organism is immensely complex. Despite this it can, to a great extent, be captured using models that assume that gene variants combine their effects in an additive manner. This thesis explores aspects of genetics that cannot be fully captured using such additive models. Using experimental data from three different model organisms, I study two phenomena that fall outside of the additive paradigm: genetic interactions and genetic variance heterogeneity. Using the model plant Arabidopsis thaliana, we show how important biological insights can be reached by exploring loci that display genetic variance heterogeneity. In the first study, this approach identified alleles in the gene CMT2 associated with the climate at sampling locations, suggesting a role in climate adaption. These alleles affected the genome wide methylation pattern, and a complete knock down of this gene increased the plants heat tolerance. In the second study, we demonstrate how the observed genetic variance heterogeneity was the result of the partial linkage of many functional alleles near the gene MOT1, all contributing to Molybdenum levels in the leaves. Further, we explore genetic interactions using data from dogs and budding yeast (Saccharomyces cerevisiae). In the dog population, two interacting loci were associated with fructosamine levels, a biomarker used to monitor blood glucose. One of the loci displayed the pattern of a selective sweep in some of the studied breeds, suggesting that the interaction is important for the phenotypic breed-differences. In a cross between two strains of yeast, with the advantage of large population size and nearly equal allele frequencies, we identified large epistatic networks. The networks were largely centered on a number of hub-loci and altogether involved hundreds of genetic interactions. Most network hubs had the ability to either suppress or uncover the phenotypic effects of other loci. Many multi-locus allele combinations resulted in phenotypes that deviated significantly from the expectations, had the loci acted in an additive manner. Critically, this thesis demonstrates that non-additive genetic mechanisms often need to be considered in order to fully understand the genetics of complex traits.
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Gunn, Melissa Rose School of Biological Earth &amp Environmental Science UNSW. "The use of microsatellites as a surrogate for quantitative trait variation in conservation." Awarded by:University of New South Wales. School of Biological, Earth and Environmental Science, 2003. http://handle.unsw.edu.au/1959.4/22457.

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Conservation biologists are interested in maintaining genetic variation in small populations, with a view to maintaining fitness and the ability of the species to adapt to changing environmental conditions. The most important type of genetic variation is therefore that which affects fitness and reproduction, and is therefore subject to natural selection. Such fitness traits are often quantitative, i.e. are the result of a suite of loci, and are continuously variable. Microsatellite markers are a popular method of determining the level of variation present in a species??? genome. The assumption is made that microsatellites, which are neutral markers, behave in the same manner as quantitative traits. If this assumption were proved incorrect, then the use of neutral markers in conservation monitoring would have to be re-evaluated. In this study, experiments have been conducted using Drosophila melanogaster to test the assumption that variation in quantitative traits under stabilising selection declines at the same rate as heterozygosity in microsatellite markers, during a population bottleneck. Experimental population bottlenecks were of two effective population sizes (Ne), Ne=2 for one generation and Ne=60 for 35 generations. Based on the effective population size, we expected both types of bottlenecks to lose 25% of neutral genetic variation. Ten replicates of each bottleneck were maintained, along with four large control populations with Ne=320. In each population, heterozygosity (He) for eight microsatellite loci was compared with the heritability and additive genetic variance of two quantitative traits subject to balancing selection: fecundity and sternopleural bristle number. Microsatellite heterozygosity decreased in accordance with neutral predictions, whereas additive genetic variation in quantitative traits altered more than expected in both large and in bottlenecked populations relative to the initial sampling values, indicating that variation in quantitative traits was not being lost at the same rate as predicted by neutral theory. For most traits, the changes in additive genetic variance were congruent in all populations, large or bottlenecked. This congruence suggests that a common process was affecting all populations, such as adaptation. A mite infestation in early generations is a possible source of selective pressure. When bottlenecked populations were compared to the contemporaneous large populations (Ne = 320), the additive genetic variance of most traits was seen to have been lost in accordance with predictions from the loss of microsatellite heterozygosity. Loss of variation in microsatellites can thus be used to predict the loss of variation in quantitative traits due to bottlenecks, but not to predict the potentially much larger changes due to other processes such as adaptation. The effects of concurrent environmental stress and reduced population size were also evaluated. Endangered populations are often subject to environmental stress in addition to reduced population size, but the effect of stress on the additive genetic variance of fitness traits in organisms undergoing population bottlenecks is unknown. If the presence of stress alters the level of additive genetic variance in fitness traits, the viability of such populations could be substantially affected. The loss of microsatellite heterozygosity was not affected by the presence of a stress agent during a bottleneck. I found some significant effects of stress on the additive genetic variance of sternopleural bristles and fecundity; there was also a significant interaction between stress and the response to directional selection in sternopleural bristles. There was also an increase in the coefficient of variation of VA for sternopleural bristles. Stress may therefore affect the manner in which populations respond to selective pressures.
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Ahmed, Helal Uddin. "Mapping stress tolerance genetic loci in Arabidopsis thaliana." Thesis, University of Newcastle Upon Tyne, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246628.

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Broadley, Simon Andrew. "The genetic analysis of a complex trait : multiple sclerosis." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620291.

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Huq, Md Nazmul. "The genetic basis of a domestication trait in the chicken: mapping quantitative trait loci for plumage colour." Thesis, Linköpings universitet, Biologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-78393.

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Domestication is the process by which animals become adapted to the environment provided by humans. The process of domestication has let to a number of correlated behavioural, morphological and physiological changes among many domesticated animal species. An example is the changes of plumage colour in the chicken. Plumage colour is one of the most readily observable traits that make distinction between breeds as well as between strains within a breed. Understanding the genetic architecture of pigmentation traits or indeed any trait is always a great challenge in evolutionary biology. The main aim of this study was to map quantitative trait loci (QTLs) affecting the red and metallic green coloration in the chicken plumage. In this study, a total of 572 F8 intercross chickens between Red Junglefowl and White Leghorn were used. Phenotypic measurements were done using a combination of digital photography and photography manipulating software. Moreover, all birds were genotyped with 657 molecular markers, covering 30 autosomes. The total map distance covered was 11228 cM and the average interval distance was 17 cM. In this analysis, a total of six QTLs (4 for red and 2 for metallic green colour) were detected on four different chromosomes: 2, 3 11 and 14. For red colour, the most significant QTL was detected on chromosome 2 at 165 cM. An additional QTL was also detected on the same chromosome at 540 cM. Two more QTLs were detected on chromosomes 11 and 14 at 24 and 203 cM respectively. Additionally, two epistatic pairs of QTLs were also detected. The identified four QTLs together can explain approximately 36% of the phenotypic variance in this trait. In addition, for metallic green colour, one significant and one suggestive QTLs were detected on chromosomes 2 and 3 at 399 and 247 cM respectively. Moreover, significant epistatic interactions between these two QTLs were detected. Furthermore, these two QTLs together can explain approximately 24% of the phenotypic variance in this trait. These findings suggest that the expression of pigmentation in the chicken plumage is highly influenced by both the epistatic actions and pleiotropic effects of different QTLs located on different chromosomes.
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Books on the topic "Genetic trait"

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Sebastian, Rachel Louise. The genetic mapping and quantitative trait analysis of Brassica Oleracea. Birmingham: University of Birmingham, 2000.

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service), ScienceDirect (Online, ed. Computational methods for genetics of complex traits. London: Academic Press, 2010.

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Maroni, Gustavo. Molecular and Genetic Analysis of Human Traits. New York: John Wiley & Sons, Ltd., 2007.

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Genes, chromosomes, and disease: From simple traits, to complex traits, to personalized medicine. Upper Saddle River, New Jersey: FT Press Science, 2011.

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Fontanesi, Luca, ed. The genetics and genomics of the rabbit. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781780643342.0000.

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Abstract The purpose of the book is to present in one location a comprehensive overview of the progress of genetics in the rabbit, with a modern vision that integrates genomics to obtain a complete picture of the state of the art and of the applications in this species, defined according to the multiple uses and multi-faceted places that this species has in applied and fundamental biology. The 18 chapters cover several fields of genetics and genomics: Chapters 1 and 2 present the rabbit within the evolutionary framework, including the systematics, its domestication and an overview of the genetic resources (breeds and lines) that have been developed after domestication. Chapters 3-5 cover the rabbit genome, cytogenetics and genetic maps and immunogenetics in this species. Chapters 6-8 present the genetics and molecular genetics of coat colours, fibre traits and other morphological traits and defects. Chapters 9-13 cover the genetics of complex traits (disease resistance, growth and meat production traits, reproduction traits), reproduction technologies and genetic improvement in the meat rabbits. Chapters 14-18 present the omics vision, the biotech and biomodelling perspectives and applications of the rabbit. This book is addressed to a broad audience, including students, teachers, researchers, veterinarians and rabbit breeders.
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Alan, Sacerdote, ed. Hope and destiny: The patient's and parent's guide to sickle cell disease and sickle cell trait. Roscoe, Ill: Hilton Pub. Co., 2002.

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Alan, Sacerdote, ed. Hope and destiny: The patient's and parent's guide to sickle cell disease and sickle cell trait. Roscoe, Ill: Hilton Pub. Co., 2006.

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Ablokov, A. V. I. Phenetics: Evolution, population, trait. New York: Columbia University Press, 1986.

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Phenetics--evolution, population, trait. New York: Columbia University Press, 1986.

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Salyers, Abigail A. Antibiotic resistance transfer in the mammalian intestinal tract. New York: Springer, 1995.

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Book chapters on the topic "Genetic trait"

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Perkins, Adam. "Genetic Influences on Personality." In The Welfare Trait, 97–111. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137555298_6.

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Cardon, Lon R. "Quantitative Trait Loci." In Behavior Genetic Approaches in Behavioral Medicine, 237–50. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4757-9377-2_13.

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Simm, Geoff, Geoff Pollott, Raphael Mrode, Ross Houston, and Karen Marshall. "Analysing genetic variation in farm animals." In Genetic improvement of farmed animals, 178–92. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789241723.0178.

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Abstract In this chapter, topics focused on how to quantify the extent to which genes affect measured traits and how to use this information in breeding programmes. Highlights include: estimating heritability; estimating non-additive parameters, correlations, and genotype by environment interactions, molecular genetics and trait variations; and calculating inbreeding using SNP markers.
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Shehzad, Tariq, and Kazutoshi Okuno. "Quantitative trait locus mapping and genetic improvement to strengthen drought tolerance in sorghum." In Molecular breeding in wheat, maize and sorghum: strategies for improving abiotic stress tolerance and yield, 433–43. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789245431.0025.

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Abstract This chapter overviews the approaches to and application of quantitative trait locus (QTL) mapping and positional cloning of genes controlling important traits related to drought tolerance in sorghum (Sorghum bicolor), which ultimately yields crop improvement and genetic modification. The use of high-throughput phenotyping will help better understand the mechanism involved in response to drought stress by plants. The new paradigm of scientific research should focus on the integration of physiology, genetics, genomics, soil characteristics and breeding to deal with the challenges of food security in the coming years.
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Millán, T., E. Madrid, P. Castro, J. Gil, and J. Rubio. "Genetic Mapping and Quantitative Trait Loci." In Compendium of Plant Genomes, 83–106. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66117-9_8.

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Luo, Yu L. L., and Huajian Cai. "The Etiology of Narcissism: A Review of Behavioral Genetic Studies." In Handbook of Trait Narcissism, 149–56. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92171-6_16.

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Correia, César, Nuno Sepúlveda, and Carlos Daniel Paulino. "Bayesian Genetic Mapping of Binary Trait Loci." In Advances in Regression, Survival Analysis, Extreme Values, Markov Processes and Other Statistical Applications, 139–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-34904-1_14.

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McWilliams, Ellen. "‘A Genetic Trait’: Alice McDermott’s Irish America." In Irishness in North American Women's Writing, 83–107. London: Palgrave Macmillan UK, 2021. http://dx.doi.org/10.1057/978-1-137-53788-1_4.

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Sharma, Gaurav, Sonia, and Atul Kumar Upadhyay. "Quantitative Genetics and the Genetic Basis for Polyphenolics Trait in Plants." In Plant Phenolics in Sustainable Agriculture, 501–15. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4890-1_21.

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Baldoni, Luciana, Bouchaib Khadari, and Raul De La Rosa. "Genetic Mapping and Detection of Quantitative Trait Loci." In Compendium of Plant Genomes, 65–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48887-5_5.

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Conference papers on the topic "Genetic trait"

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Будак, Александр, and Олег Харчук. "Изучение влияния условий года и генотипа на вариабельность и наследуемость количественного признака высота растения и связанных с ним признаков у сои." In International Scientific Symposium "Plant Protection – Achievements and Prospects". Institute of Genetics, Physiology and Plant Protection, Republic of Moldova, 2020. http://dx.doi.org/10.53040/9789975347204.76.

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The variability of traits is the height of the plant and the average length of the internode to a greater extent influenced by the genotype. The good heritability of these traits is evidenced by the high heritability rates for these traits. The variability of the attachment height of the lower pod is more influenced by the conditions of the year, the heritability coefficient is lower than that of the previous traits. Genetic progress is the highest (40.33%) among the studied traits in the trait with an average internode length, which indicates that selection for this trait may be the most successful.
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Mutalib, Sofianita, Shuzlina Abdul-Rahman, and Azlinah Mohamed. "Applying rule classifiers in predicting trait from genetic variants." In 2012 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES 2012). IEEE, 2012. http://dx.doi.org/10.1109/iecbes.2012.6498197.

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Wu, Dongrui. "Genetic algorithm based feature selection for speaker trait classification." In Interspeech 2012. ISCA: ISCA, 2012. http://dx.doi.org/10.21437/interspeech.2012-96.

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De Carlo, Matteo, Eliseo Ferrante, and A. E. Eiben. "Comparing indirect encodings by evolutionary attractor analysis in the trait space of modular robots." In GECCO '20: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3377929.3390032.

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Saputro, Nico, and Veronica S. Moertini. "Guiding Genetic Algorithm via Viral Trait Spreading for Solving Sudoku Puzzle." In 2011 First International Conference on Informatics and Computational Intelligence (ICI). IEEE, 2011. http://dx.doi.org/10.1109/ici.2011.33.

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Ogundijo, Oyetunji E., Dan He, and Laxmi Parida. "Performance evaluation of different encoding strategies for quantitative genetic trait prediction." In 2015 IEEE 5th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2015. http://dx.doi.org/10.1109/iccabs.2015.7344715.

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Lu, Hong, and Lu Lu. "Expression quantitative trait loci and genetic regulatory network analysis of Fbn1." In INTERNATIONAL SYMPOSIUM ON THE FRONTIERS OF BIOTECHNOLOGY AND BIOENGINEERING (FBB 2019). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5110812.

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Dan He and Laxmi Parida. "Does encoding matter? A novel view on the quantitative genetic trait prediction problem." In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2015. http://dx.doi.org/10.1109/bibm.2015.7359667.

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HE, DAN, and LAXMI PARIDA. "MUSE: A MULTI-LOCUS SAMPLING-BASED EPISTASIS ALGORITHM FOR QUANTITATIVE GENETIC TRAIT PREDICTION." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2016. http://dx.doi.org/10.1142/9789813207813_0040.

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Han, Jian-ming, Rui-ling Wang, Yan-wei Cheng, Xue-bin Li, and Chao-jun He. "Genetic analysis of leaf expansion trait in Brassica rapa L. ssp. chinensis (L.) Hanelt." In 2013 7th International Conference on Systems Biology (ISB). IEEE, 2013. http://dx.doi.org/10.1109/isb.2013.6623783.

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Reports on the topic "Genetic trait"

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Vermerris, Wilfred, Stephen Kresovich, Seth Murray, Jeffery Pedersen, William Rooney, and Scott Sattler. Genetic dissection of bioenerrgy traits in sorghum. Office of Scientific and Technical Information (OSTI), June 2012. http://dx.doi.org/10.2172/1062561.

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Fan, Bin, Suneel K. Onteru, Marja Nikkilä, Kenneth J. Stalder, and Max F. Rothschild. Identification of Genetic Markers Associated with Sow Reproductive and Longevity Traits. Ames (Iowa): Iowa State University, January 2009. http://dx.doi.org/10.31274/ans_air-180814-928.

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Serão, Nick V. L., Oswald Matika, Steve Bishop, Bob Kemp, John Harding, Graham Plastow, and Jack C. M. Dekkers. Genetic Analysis of Reproductive Traits and Antibody Response in PRRS Infected Sows. Ames (Iowa): Iowa State University, January 2014. http://dx.doi.org/10.31274/ans_air-180814-1362.

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Schwab, Clint R., and Thomas J. Baas. Genetic Parameter Estimates of Production, Meat Quality, and Sensory Traits in Duroc Swine. Ames (Iowa): Iowa State University, January 2008. http://dx.doi.org/10.31274/ans_air-180814-64.

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Tait, Richard G., Shu Zhang, Travis Knight, Daryl R. Strohbehn, Donald C. Beitz, and James M. Reecy. Genetic Correlations of Fatty Acid Concentrations with Carcass Traits in Angus-Sired Beef Cattle. Ames (Iowa): Iowa State University, January 2008. http://dx.doi.org/10.31274/ans_air-180814-501.

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Nikkilä, Marja, Kenneth J. Stalder, Benny E. Mote, Jay Lampe, Bridget Thorn, Max F. Rothschild, Anna K. Johnson, Locke A. Karriker, and Timo Serenius. Heritabilities and Genetic Correlations of Body Composition and Structural Soundness Traits in Commercial Gilts. Ames (Iowa): Iowa State University, January 2008. http://dx.doi.org/10.31274/ans_air-180814-147.

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Rajarajan, Kunasekaran, Alka Bharati, Hirdayesh Anuragi, Arun Kumar Handa, Kishor Gaikwad, Nagendra Kumar Singh, Kamal Prasad Mohapatra, et al. Status of perennial tree germplasm resources in India and their utilization in the context of global genome sequencing efforts. World Agroforestry, 2020. http://dx.doi.org/10.5716/wp20050.pdf.

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Tree species are characterized by their perennial growth habit, woody morphology, long juvenile period phase, mostly outcrossing behaviour, highly heterozygosity genetic makeup, and relatively high genetic diversity. The economically important trees have been an integral part of the human life system due to their provision of timber, fruit, fodder, and medicinal and/or health benefits. Despite its widespread application in agriculture, industrial and medicinal values, the molecular aspects of key economic traits of many tree species remain largely unexplored. Over the past two decades, research on forest tree genomics has generally lagged behind that of other agronomic crops. Genomic research on trees is motivated by the need to support genetic improvement programmes mostly for food trees and timber, and develop diagnostic tools to assist in recommendation for optimum conservation, restoration and management of natural populations. Research on long-lived woody perennials is extending our molecular knowledge and understanding of complex life histories and adaptations to the environment, enriching a field that has traditionally drawn its biological inference from a few short-lived herbaceous species. These concerns have fostered research aimed at deciphering the genomic basis of complex traits that are related to the adaptive value of trees. This review summarizes the highlights of tree genomics and offers some priorities for accelerating progress in the next decade.
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Tuggle, Christopher K., Xian-wei Shi, Lena Marklund, Amber Stumbaugh, Thomas J. Stabel, Martha A. Mellencamp, Lucina Galina-Pantoja, and John Bastiaansen. Association of bacterial infection traits with genetic variation at candidate genes for porcine disease resistance. Ames (Iowa): Iowa State University, January 2004. http://dx.doi.org/10.31274/ans_air-180814-30.

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Abell, Caitlyn, Kenneth J. Stalder, and John W. Mabry. Genetic and Phenotypic Correlations for Maternal and Postweaning Traits from a Seedstock Swine Breeding System. Ames (Iowa): Iowa State University, January 2011. http://dx.doi.org/10.31274/ans_air-180814-878.

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Su, Hailin, Dorian J. Garrick, Bruce Golden, and Lauren Hyde. Estimation of Genetic Parameters for Carcass Traits and Their Corresponding Ultrasound Measurements in Crossbred Beef Cattle. Ames (Iowa): Iowa State University, January 2016. http://dx.doi.org/10.31274/ans_air-180814-486.

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