Relevant bibliographies by topics / Complex Traits Genetics

Academic literature on the topic 'Complex Traits Genetics'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Complex Traits Genetics"

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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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Kemper, Kathryn. "59 Insights into Complex Traits from Human Genetics." Journal of Animal Science 99, Supplement_3 (October 8, 2021): 30–31. http://dx.doi.org/10.1093/jas/skab235.052.

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Abstract Genomic selection has been implemented successfully in many livestock industries for genetic improvement. However, genomic selection provides limited insight into the genetic mechanisms underlying variation in complex traits. In contrast, human genetics has a focus on understanding genetic architecture and the origins of quantitative trait variation. This presentation will discuss a number of examples from human genetics which can inform our understanding of the nature of variation in complex traits. So-called ‘monogenic’ conditions, for example, are proving to have more complex genetic architecture than naïve expectations might suggest. Massive data sets of millions of people are also enabling longstanding questions to be addressed. Traits such as height, for example, are affected by a very large but finite number of loci. We can reconcile seemingly disparate heritability estimates from different experimental designs by accounting for assortative mating. The presentation will provide a brief update on current approaches to genomic prediction in human genetics and discuss the implications of these findings for understanding and predicting complex traits in livestock.
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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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Yi, Nengjun, and Shizhong Xu. "Bayesian Mapping of Quantitative Trait Loci for Complex Binary Traits." Genetics 155, no. 3 (July 1, 2000): 1391–403. http://dx.doi.org/10.1093/genetics/155.3.1391.

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AbstractA complex binary trait is a character that has a dichotomous expression but with a polygenic genetic background. Mapping quantitative trait loci (QTL) for such traits is difficult because of the discrete nature and the reduced variation in the phenotypic distribution. Bayesian statistics are proved to be a powerful tool for solving complicated genetic problems, such as multiple QTL with nonadditive effects, and have been successfully applied to QTL mapping for continuous traits. In this study, we show that Bayesian statistics are particularly useful for mapping QTL for complex binary traits. We model the binary trait under the classical threshold model of quantitative genetics. The Bayesian mapping statistics are developed on the basis of the idea of data augmentation. This treatment allows an easy way to generate the value of a hypothetical underlying variable (called the liability) and a threshold, which in turn allow the use of existing Bayesian statistics. The reversible jump Markov chain Monte Carlo algorithm is used to simulate the posterior samples of all unknowns, including the number of QTL, the locations and effects of identified QTL, genotypes of each individual at both the QTL and markers, and eventually the liability of each individual. The Bayesian mapping ends with an estimation of the joint posterior distribution of the number of QTL and the locations and effects of the identified QTL. Utilities of the method are demonstrated using a simulated outbred full-sib family. A computer program written in FORTRAN language is freely available on request.
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Goddard, M. E., K. E. Kemper, I. M. MacLeod, A. J. Chamberlain, and B. J. Hayes. "Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture." Proceedings of the Royal Society B: Biological Sciences 283, no. 1835 (July 27, 2016): 20160569. http://dx.doi.org/10.1098/rspb.2016.0569.

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Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.
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Cooper, Mark, Dean W. Podlich, and Oscar S. Smith. "Gene-to-phenotype models and complex trait genetics." Australian Journal of Agricultural Research 56, no. 9 (2005): 895. http://dx.doi.org/10.1071/ar05154.

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The premise that is explored in this paper is that in some cases, in order to make progress in the design of molecular breeding strategies for complex traits, we will need a theoretical framework for quantitative genetics that is grounded in the concept of gene-networks. We seek to develop a gene-to-phenotype (G→P) modelling framework for quantitative genetics that explicitly deals with the context-dependent gene effects that are attributed to genes functioning within networks, i.e. epistasis, gene × environment interactions, and pleiotropy. The E(NK) model is discussed as a starting point for building such a theoretical framework for complex trait genetics. Applying this framework to a combination of theoretical and empirical G→P models, we find that although many of the context-dependent effects of genetic variation on phenotypic variation can reduce the rate of genetic progress from breeding, it is possible to design molecular breeding strategies for complex traits that on average will outperform phenotypic selection. However, to realise these potential advantages, empirical G→P models of the traits will need to take into consideration the context-dependent effects that are a consequence of epistasis, gene × environment interactions, and pleiotropy. Some promising G→P modelling directions are discussed.
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Kučera, L. "D.C. Rao & M.A. Province – Advances in Genetics,Vol. 42, Genetic Dissection of Complex Traits." Czech Journal of Genetics and Plant Breeding 38, No. 1 (July 30, 2012): 64. http://dx.doi.org/10.17221/6112-cjgpb.

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Hackinger, Sophie, and Eleftheria Zeggini. "Statistical methods to detect pleiotropy in human complex traits." Open Biology 7, no. 11 (November 2017): 170125. http://dx.doi.org/10.1098/rsob.170125.

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In recent years pleiotropy, the phenomenon of one genetic locus influencing several traits, has become a widely researched field in human genetics. With the increasing availability of genome-wide association study summary statistics, as well as the establishment of deeply phenotyped sample collections, it is now possible to systematically assess the genetic overlap between multiple traits and diseases. In addition to increasing power to detect associated variants, multi-trait methods can also aid our understanding of how different disorders are aetiologically linked by highlighting relevant biological pathways. A plethora of available tools to perform such analyses exists, each with their own advantages and limitations. In this review, we outline some of the currently available methods to conduct multi-trait analyses. First, we briefly introduce the concept of pleiotropy and outline the current landscape of pleiotropy research in human genetics; second, we describe analytical considerations and analysis methods; finally, we discuss future directions for the field.
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Belmont, John W., and Suzanne M. Leal. "Complex phenotypes and complex genetics: An introduction to genetic studies of complex traits." Current Atherosclerosis Reports 7, no. 3 (May 2005): 180–87. http://dx.doi.org/10.1007/s11883-005-0004-6.

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Parker, Katherine, A. Mesut Erzurumluoglu, and Santiago Rodriguez. "The Y Chromosome: A Complex Locus for Genetic Analyses of Complex Human Traits." Genes 11, no. 11 (October 29, 2020): 1273. http://dx.doi.org/10.3390/genes11111273.

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The Human Y chromosome (ChrY) has been demonstrated to be a powerful tool for phylogenetics, population genetics, genetic genealogy and forensics. However, the importance of ChrY genetic variation in relation to human complex traits is less clear. In this review, we summarise existing evidence about the inherent complexities of ChrY variation and their use in association studies of human complex traits. We present and discuss the specific particularities of ChrY genetic variation, including Y chromosomal haplogroups, that need to be considered in the design and interpretation of genetic epidemiological studies involving ChrY.
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Dissertations / Theses on the topic "Complex Traits Genetics"

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Bell, Jordana Tzenova. "Epistasis in complex human traits." Thesis, University of Oxford, 2006. http://ora.ox.ac.uk/objects/uuid:547db446-c84c-4a6c-8b5c-ce960f7765c5.

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Nelson, Vicki R. "Transgenerational Genetic Effects In Mouse Models Of Complex Traits." Case Western Reserve University School of Graduate Studies / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=case1278706008.

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Goddard, Katrina Blouke. "Study design issues in the analysis of complex genetic traits /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/9565.

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Joshi, Peter K. "Exploring the inheritance of complex traits in humans." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/21118.

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I explore the genetic and environmental basis of inheritance using modern techniques, in particular high-density genotyping arrays, and older techniques, in particular family history, to explore some longstanding questions about the way we inherit complex traits. Using pedigree data and the parent-offspring regression technique, I estimate narrow sense heritability (h2) of human lifespan in 20th Century Scotland as 0.16, lower than commonly cited studies in other populations. I also observe similar concordance between spouses as between parents and offspring - suggesting my estimate of heritability may include significant within-family environment effects and thus should be considered an upper bound. Using genome-wide array data to identify runs of homozygosity, from 150 cohorts across the world and up to 350,000 subjects per trait, I show that cognitive function and body size are associated with the total length of genome-wide runs of homozygosity. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of homozygosity on blood pressure and low-density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. An association between genome-wide homozygosity and complex traits arises due to directional dominance. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases have not. The analysis of less common single nucleotide polymorphism (SNP) variants in genome-wide association studies promises to elucidate complex trait genetics but is hampered by low power to reliably detect association, whilst avoiding false positives. I show that addition of 100 population-specific exome sequences to 1,000 genomes global reference data allows more accurate imputation, particularly of less common SNPs (minor allele frequency 1–10%). The imputation improvement corresponds to an increase in effective sample size of 28–38%, for SNPs with a minor allele frequency in the range 1–3%. Inheritance of complex traits remains a field wide open for discovery, both in determining the balance between nature and nurture and discovery of the specific mechanisms by which DNA causes variation in these traits, with the prospect of such discoveries illuminating biological pathways involved and, as knowledge deepens, facilitating prediction.
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Allchin, Lorraine Doreen May. "Statistical methods for mapping complex traits." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:65f392ba-1b64-4b00-8871-7cee98809ce1.

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The first section of this thesis addresses the problem of simultaneously identifying multiple loci that are associated with a trait, using a Bayesian Markov Chain Monte Carlo method. It is applicable to both case/control and quantitative data. I present simulations comparing the methods to standard frequentist methods in human case/control and mouse QTL datasets, and show that in the case/control simulations the standard frequentist method out performs my model for all but the highest effect simulations and that for the mouse QTL simulations my method performs as well as the frequentist method in some cases and worse in others. I also present analysis of real data and simulations applying my method to a simulated epistasis data set. The next section was inspired by the challenges involved in applying a Markov Chain Monte Carlo method to genetic data. It is an investigation into the performance and benefits of the Matlab parallel computing toolbox, specifically its implementation of the Cuda programing language to Matlab's higher level language. Cuda is a language which allows computational calculations to be carried out on the computer's graphics processing unit (GPU) rather than its central processing unit (CPU). The appeal of this tool box is its ease of use as few code adaptions are needed. The final project of this thesis was to develop an HMM for reconstructing the founders of sparsely sequenced inbred populations. The motivation here, that whilst sequencing costs are rapidly decreasing, it is still prohibitively expensive to fully sequence a large number of individuals. It was proposed that, for populations descended from a known number of founders, it would be possible to sequence these individuals with a very low coverage, use a hidden Markov model (HMM) to represent the chromosomes as mosaics of the founders, then use these states to impute the missing data. For this I developed a Viterbi algorithm with a transition probability matrix based on recombination rate which changes for each observed state.
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Luo, Yuqun. "Incorporation of genetic marker information in estimating model parameters for complex traits with data from large complex pedigrees /." The Ohio State University, 2002. http://rave.ohiolink.edu/etdc/view?acc_num=osu1486549482668451.

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Bigdeli, T. Bernard. "Quantitative Genetic Methods to Dissect Heterogeneity in Complex Traits." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2651.

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Etiological models of complex disease are elusive[46, 33, 9], as are consistently replicable findings for major genetic susceptibility loci[54, 14, 15, 24]. Commonly-cited explanations invoke low-frequency genomic variation[41], allelic heterogeneity at susceptibility loci[33, 30], variable etiological trajectories[18, 17], and epistatic effects between multiple loci; these represent among the most methodologically-challenging issues in molecular genetic studies of complex traits. The response has been con- sistently reactionary—hypotheses regarding the relative contributions of known func- tional elements, or emphasizing a greater role of rare variation[46, 33] have undergone periodic revision, driving increasingly collaborative efforts to ascertain greater numbers of participants and which assay a rapidly-expanding catalogue of human genetic variation. Major deep-sequencing initiatives, such as the 1,000 Genomes Project, are currently identifying human polymorphic sites at frequencies previously unassailable and, not ten years after publication of the first major genome-wide association find- ings, re-sequencing has already begun to displace GWAS as the standard for genetic analysis of complex traits. With studies of complex disease primed for an unprecedented survey of human genetic variation, it is essential that human geneticists address several prominent, problematic aspects of this research. Realizations regarding the boundaries of human traits previously considered to be effectively disparate in presentation[44, 39, 35, 27, 25, 12, 4, 13], as well as profound insight into the extent of human genetic diversity[23, 22] are not without consequence. Whereas the resolution of fine-mapping studies have undergone persistent refinement, recent polygenic findings suggest a less discriminant basis of genetic liability, raising the question of what a given, unitary association finding actually represents. Furthermore, realistic expectations regarding the pattern of findings for a particular genetic factor between or even within populations remain unclear. Of interest herein are methodologies which exploit the finite extent of genomic variability within human populations to distinguish single-point and cumulative group differences in liability to complex traits, the range of allele frequencies for which common association tests are appropriate, and the relevant dimensionality of common genetic variation within ethnically-concordant but differentially ascertained populations. Using high-density SNP genotype data, we consider both hypothesis-driven and agnostic (genome-wide) approaches to association analysis, and address specific issues pertaining to empirical significance and the statistical properties of commonly- applied tests. Lastly, we demonstrate a novel perspective of genome-wide genetic “background” through exhaustive evaluation of fundamental, stochastic genetic processes in a sample of matched affected and unaffected siblings selected from high- density schizophrenia families.
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Ashbrook, David. "A systems-genetics analyses of complex phenotypes." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/a-systemsgenetics-analyses-of-complex-phenotypes(a3e7ad8e-b23b-40fd-821e-26a6c1a63d38).html.

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Complex phenotypes are traits which are influenced by many factors, and not just a single gene, as for classical Mendelian traits. The brain, and its resultant behaviour, gives us a large subset of complex phenotypes to examine. Variation in these traits is affected by a range of different influences, both genetic and environmental, including social interactions and the effects of parents. Systems-genetics provides us with a framework in which to examine these complex traits, seeking to connect genetic variants to the phenotypes they cause, through intermediate phenotypes, such as gene expression and protein levels. This approach has been developed to exploit and analyse massive data sets generated for example in genomics and transcriptomics. In the first half of this thesis, I combine genetic linkage data from the BXD recombinant inbred mouse panel with genome-wide association data from humans to identify novel candidate genes, and use online gene annotations and functional descriptions to support these candidates. Firstly, I discovered MGST3 as a novel regulator of hippocampus size, which may be linked to neurodegenerative disorders. Secondly, I identified that CMYA5, MCTP1, TNR and RXRG are associated with mouse anxiety-like phenotypes and human bipolar disorder, and provide evidence that MCTP1, TNR and RXRG may be acting via inter-cellular signalling in the striatum. The second half of this thesis uses different cross-fostering designs between genetically variable BXD lines and the genetically uniform C57BL/6J strain to identify indirect genetic effects and the loci underlying them. With this, I have found novel loci expressed in mothers that alter offspring behaviour, novel loci expressed in offspring affecting the level of maternal care, and novel loci expressed in offspring, which alter the behaviour of their nestmates, as well as the level of maternal care they receive. Further I provide evidence of co-adaptation between maternal and offspring genotypes, and a positive indirect genetic effect of offspring on their nestmates, supportive of a role for kin selection. Finally, I demonstrate that the BXD lines can be used to investigate genes with parent-of-origin dependent expression, which have an indirect genetic effect on maternal care. In conclusion, this thesis identifies a number of novel loci, and in some cases genes, associated with complex traits. Not only are these techniques applicable to other phenotypes and other questions, but the candidates I identify can now be examined further in vitro or in vivo.
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Valenzuela, Robert Keams. "Predictive Modeling for Complex Traits: Normal Human Pigmentation Variation." Diss., The University of Arizona, 2011. http://hdl.handle.net/10150/145309.

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Melanin pigmentation is a complex trait governed by many genes. Variation in melanin pigmentation within, and between, populations makes it an important trait for assisting in physical identification of an individual in forensic investigations. Utilizing a training sample (n=789) comprised of various ethnicities and SNPs (75) in 24 genes previously implicated in human or animal pigmentation studies, I determined three-SNP multiple linear regression models that accounted for large proportions of pigmentation variation in skin (45.7%), eye color (76.4%), and hair [eumelanin-to-pheomelanin (43.2%) and total melanin (76.3%)], independent of ethnic origin. Rather than implementing stepwise regression, to ascertain the three-SNP predictive models, I devised an algorithm that is likely more robust than stepwise regression. The algorithm consisted of two steps: the first step reduced the pool of 75 SNPs to a pool of 40 by selection of SNPs that were significant (p<0.05) by one-way ANOVA; the second step enabled selection of SNPs for model incorporation based on their frequency in the best-fitted models of all possible combinations of three-SNP models (i.e., 40 choose 3).Prediction models were validated utilizing an independent cohort (n=242, test sample) that was very similar in ethnic composition to the training sample. Relative shrinkage was moderate for skin reflectance (23.4%), eye color (19.4%), and eumelanin-to-pheomelanin (37.3%) of hair, and largest for total melanin (67%) of hair. Additionally, we refined our model-building algorithm, enabling visual comparison of the frequency and co-linearity due to linkage or co-inheritance of SNPs of the best-fitted models. Application of our algorithm to the test sample yielded the same or similar models as the training sample. Two of the three SNPs composing the models were the same, with some variability in the third SNP of the model.
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Uricchio, Lawrence Hart. "Models and forward simulations of selection, human demography, and complex traits." Thesis, University of California, San Francisco, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3681226.

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Evolutionary forces such as recombination, demography, and selection can shape patterns of genetic diversity within populations and contribute to phenotypic variation. While theoretical models exist for each of these forces independently, mathematically modeling their joint impact on patterns of genetic diversity remains very challenging. Fortunately, it is possible to perform forward-in-time computer simulations of DNA sequences that incorporate all of these forces simultaneously. Here, I show that there are trade-offs between computational efficiency and accuracy for simulations of a widely investigated model of recurrent positive selection. I develop a theoretical model to explain this trade-off, and a simple algorithm that obtains the best possible computational performance for a given error tolerance. I then pivot to develop a framework for simulations of human DNA sequences and genetically complex phenotypes, incorporating recently inferred demographic models of human continental groups and selection on genes and non-coding elements. I use these simulations to investigate the power of rare variant association tests in the context of rampant selection and non-equilibrium demography. I show that the power of rare variant association tests is in some cases quite sensitive to underlying assumptions about the relationship between selection and effect sizes. This work highlights both the challenge and the promise of applying forward simulations in genetic studies that seek to infer the parameters of evolutionary models and detect statistical associations.

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Books on the topic "Complex Traits Genetics"

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

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1960-, Paterson Andrew H., ed. Molecular dissection of complex traits. Boca Raton, Fla: CRC Press, 1998.

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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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C, Rao D., and Province Michael Arthur, eds. Genetic dissection of complex traits. San Diego: Academic Press, 2001.

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1947-, Fischer Ernst Peter, Hood Leroy E, and Möller Gerald, eds. Complex traits. München: Piper, 1997.

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Genetic Dissection of Complex Traits, Volume 60. 2nd ed. Academic Press, 2008.

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C, Rao D., and Gu C. Charles, eds. Genetic dissection of complex traits. 2nd ed. London: Academic Press, 2008.

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Rao, D. C. Genetic Dissection of Complex Traits. Elsevier Science & Technology Books, 2000.

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Rao, D. C., and C. Charles Gu. Genetic Dissection of Complex Traits. Elsevier Science & Technology Books, 2008.

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Book chapters on the topic "Complex Traits Genetics"

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Bailey, Ernest, and Samantha A. Brooks. "Genetics of complex traits." In Horse genetics, 188–96. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781786392589.0188.

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Carter, Gregory W., and Aimée M. Dudley. "Systems Genetics and Complex Traits." In Encyclopedia of Complexity and Systems Science, 9105–24. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-0-387-30440-3_549.

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Toland, Amanda Ewart. "Interaction Between Genetics and Epigenetics in Cancer." In Epigenetics and Complex Traits, 209–29. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_9.

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Labbe, Aurélie, Lam Opal Huang, and Claire Infante-Rivard. "Transmission Ratio Distortion: A Neglected Phenomenon with Many Consequences in Genetic Analysis and Population Genetics." In Epigenetics and Complex Traits, 265–85. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_12.

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Gonzalo, María José, and Antonio J. Monforte. "Genetic Mapping of Complex Traits in Cucurbits." In Genetics and Genomics of Cucurbitaceae, 269–90. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/7397_2016_9.

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Grigorenko, Elena L. "Epistasis and the genetics of complex traits." In Behavioral genetics in the postgenomic era., 247–66. Washington: American Psychological Association, 2003. http://dx.doi.org/10.1037/10480-014.

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Huang, Xuehui, and Bin Han. "Genome-Wide Association Mapping of Complex Traits in Rice." In Rice Genomics, Genetics and Breeding, 497–510. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7461-5_25.

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Rao, D. C., and P. P. Majumder. "Genetics of Complex Traits with Particular Attention to Fat Patterning." In Perspectives in Human Growth, Development and Maturation, 79–89. Dordrecht: Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-015-9801-9_7.

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Flannick, Jason, and William L. Lowe. "SLC30A8: A Complex Road from Association to Function." In The Genetics of Type 2 Diabetes and Related Traits, 379–401. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-01574-3_18.

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Beckmann, Jacques S., and Stylianos E. Antonarakis. "Lessons from the Genome-Wide Association Studies for Complex Multifactorial Disorders and Traits." In Vogel and Motulsky's Human Genetics, 287–97. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-37654-5_10.

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Conference papers on the topic "Complex Traits Genetics"

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"Genome-wide association and epistatic scan for unravelling the genetic architecture of complex traits and their practical applications in a breeding program." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-158.

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Karkar, Slim, Yann Le Guen, Cathy Philippe, Claire Dandine-Roulland, Morgane Pierre-Jean, Jean-FranCois Mangin, Edith Le Floch, and Vincent Frouin. "A study of feasibility for genome-wide haplotype association of complex traits in imaging genetics." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621306.

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Novohatin, Vladimir, Vladimir Vorob'ev, and Viktor Dragavcev. "New algorithms of phenotyping for seven genetic-physiological systems which maximising yield of future varieties." In Multifunctional adaptive fodder production. ru: Federal Williams Research Center of Forage Production and Agroecology, 2022. http://dx.doi.org/10.33814/mak-2022-28-76-103-115.

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Improvement of hereditary drought resistance in crops is recently being among the main objectives for food security of humanity because of global warming and the growing costs for bakery and forage grain. Analysis of complex properties of drought resistance in cereal (phenotyping) shows the limitation of a canonical genocentric approach and the approaches based on molecular genetics to solve the problem of significant hereditary improvement of drought resistance. The priority epigenetic approach that we propose is based on the Theory of eco-genetic organization of quantitative traits (TEGOQT). In TEGOQT seven genetic-physiological systems (GPS) involved in harvest increasing, but not particular traits of product ivity, are to be operated with. These GPS are attractions; micro-distribution of attractive plastics substances between grains and chaff in ear; adaptability to drought, cold, frost, heat, salt, etc; horizontal immunity; ''payment'' by dry biomass for a limiting factor of soil nutrition — N, P, K, etc.; tolerance to plant density in phytocenosis; hereditary variability in duration of the phases of ontogenesis. In this paper we discuss drought adaptability as a part of GPS complex. It is shown that phenotyping evaluation is necessary to analize drought tolerance, the complex property to which no less than 22 components characters contribute.
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Gaina, Boris, and Eugeniu Alexandrov. "Compușii chimici volatili și noile genotipuri de viță-de-vie." In VIIth International Scientific Conference “Genetics, Physiology and Plant Breeding”. Institute of Genetics, Physiology and Plant Protection, Republic of Moldova, 2021. http://dx.doi.org/10.53040/gppb7.2021.36.

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In the process of development and ripening of berries, depending on fluctuations in climatic fac-tors, an aroma characteristic of the genotype of grapevine is formed, and as a result of processing the bunches, a bouquet of young wine is formed. Grapevine berries contain, for the most part, the same aro-matic chemical compounds, however, the specific aroma is due not only to their different mass concentra-tion, but also to their ratio in the aromatic complex of each genotype. The specific shade of aromas of a particular genotype and the accent of aromas of a particular genotype depends to a greater extent on the transmission of hereditary traits from parental pairs of crossing, the degree of ripening of berries, the phy-tosanitary level of plantings and on the influence of factors of the growing environment. The purpose of this study is to determine and comparative analysis of aromatic compounds in the berries of the rhizogen-ic interspecific genotype of grapevine Amethyst with the same complex of volatile compounds of the classic varieties Feteasca Neagră, Cabernet-Sauvignon, Malbec.
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BARBOSA, FERNANDA B., LUCIANA DE OLIVEIRA, NAILU A. SINICATO, ROBERTO MARINI, VERA L. GIL-DA-SILVA-LOPES, and SIMONE APPENZELLER. "GENETIC ANCESTRY AND ITS CONTRIBUTION TO COMPLEX TRAITS IN CHILDHOOD-ONSET SYSTEMIC LUPUS ERYTHEMATOSUS." In 36º Congresso Brasileiro de Reumatologia. São Paulo: Editora Blucher, 2019. http://dx.doi.org/10.5151/sbr2019-460.

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Wang, Lu-yong, and Daniel Fasulo. "A Fast Boosting-Based Screening Method for Large-scale Association Study in Complex Traits with Genetic Heterogeneity." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.260585.

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Wang, Lu-yong, and Daniel Fasulo. "A Fast Boosting-Based Screening Method for Large-scale Association Study in Complex Traits with Genetic Heterogeneity." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4398768.

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Pavanello, Sofia, Giuseppe Mastrangelo, Manuela Campisi, Angela Carta, Cecilia Arici, and Stefano Porru. "P129 Role of telomere length within the complex relationship between genetic traits and environmental/occupational exposures in bladder cancer risk." In Occupational Health: Think Globally, Act Locally, EPICOH 2016, September 4–7, 2016, Barcelona, Spain. BMJ Publishing Group Ltd, 2016. http://dx.doi.org/10.1136/oemed-2016-103951.446.

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HALL, MOLLY A., SHEFALI SETIA VERMA, DENNIS P. WALL, JASON H. MOORE, BRENDAN KEATING, DANIEL B. CAMPBELL, GREGORY GIBSON, FOLKERT W. ASSELBERGS, and SARAH PENDERGRASS. "SESSION INTRODUCTION: CHARACTERIZING THE IMPORTANCE OF ENVIRONMENTAL EXPOSURES, INTERACTIONS BETWEEN THE ENVIRONMENT AND GENETIC ARCHITECTURE, AND GENETIC INTERACTIONS: NEW METHODS FOR UNDERSTANDING THE ETIOLOGY OF COMPLEX TRAITS AND DISEASE." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2014. http://dx.doi.org/10.1142/9789814644730_0016.

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Kasakova, A. S., and A. G. Galayan. "METHODS OF TRANSCRIPTOMICS FOR CEREALS’ STUDY." In STATE AND DEVELOPMENT PROSPECTS OF AGRIBUSINESS. DSTU-PRINT, 2020. http://dx.doi.org/10.23947/interagro.2020.1.579-582.

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Wheat is a crop that feeds millions, and its yield is determined by economic, climatic, and genetic factors. Unfortunately, the productivity of grain in fact does not always correspond to the desired result. Transcriptomics is a universal and modern method of solving complex and topical issues facing scientists for many centuries. Analysis of the expression of genes associated with the state of rest and germination of grain in wheat embryos is of great agronomic interest, since this process is directly related to the deterioration of the quality and decrease in the yield of grain before harvest. The difficulty of isolating RNA from a small amount of tissue is an obstacle to analyzing gene expression. Difficulty isolating RNA from a small amount of tissue. The developed new methods for the analysis of transcripts in an individual family make it possible to plan the creation of cultivars of agricultural crops. crops with specified traits.
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Reports on the topic "Complex Traits Genetics"

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Cahaner, Avigdor, Susan J. Lamont, E. Dan Heller, and Jossi Hillel. Molecular Genetic Dissection of Complex Immunocompetence Traits in Broilers. United States Department of Agriculture, August 2003. http://dx.doi.org/10.32747/2003.7586461.bard.

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Objectives: (1) Evaluate Immunocompetence-OTL-containing Chromosomal Regions (ICRs), marked by microsatellites or candidate genes, for magnitude of direct effect and for contribution to relationships among multiple immunocompetence, disease-resistance, and growth traits, in order to estimate epistatic and pleiotropic effects and to predict the potential breeding applications of such markers. (2) Evaluate the interaction of the ICRs with genetic backgrounds from multiple sources and of multiple levels of genetic variation, in order to predict the general applicability of molecular genetic markers across widely varied populations. Background: Diseases cause substantial economic losses to animal producers. Emerging pathogens, vaccine failures and intense management systems increase the impact of diseases on animal production. Moreover, zoonotic pathogens are a threat to human food safety when microbiological contamination of animal products occurs. Consumers are increasingly concerned about drug residues and antibiotic- resistant pathogens derived from animal products. The project used contemporary scientific technologies to investigate the genetics of chicken resistance to infectious disease. Genetic enhancement of the innate resistance of chicken populations provides a sustainable and ecologically sound approach to reduce microbial loads in agricultural populations. In turn, animals will be produced more efficiently with less need for drug treatment and will pose less of a potential food-safety hazard. Major achievements, conclusions and implications:. The PI and co-PIs had developed a refined research plan, aiming at the original but more focused objectives, that could be well-accomplished with the reduced awarded support. The successful conduct of that research over the past four years has yielded substantial new information about the genes and genetic markers that are associated with response to two important poultry pathogens, Salmonella enteritidis (SE) and Escherichia coli (EC), about variation of immunocompetence genes in poultry, about relationships of traits of immune response and production, and about interaction of genes with environment and with other genes and genetic background. The current BARD work has generated a base of knowledge and expertise regarding the genetic variation underlying the traits of immunocompetence and disease resistance. In addition, unique genetic resource populations of chickens have been established in the course of the current project, and they are essential for continued projects. The US laboratory has made considerable progress in studies of the genetics of resistance to SE. Microsatellite-marked chromosomal regions and several specific genes were linked to SE vaccine response or bacterial burden and the important phenomenon of gene interaction was identified in this system. In total, these studies demonstrate the role of genetics in SE response, the utility of the existing resource population, and the expertise of the research group in conducting such experiments. The Israeli laboratories had showed that the lines developed by selection for high or low level of antibody (Ab) response to EC differ similarly in Ab response to several other viral and bacterial pathogens, indicating the existence of a genetic control of general capacity of Ab response in young broilers. It was also found that the 10w-Ab line has developed, possibly via compensatory "natural" selection, higher cellular immune response. At the DNA levels, markers supposedly linked to immune response were identified, as well as SNP in the MHC, a candidate gene responsible for genetic differences in immunocompetence of chickens.
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Hulata, Gideon, and Graham A. E. Gall. Breed Improvement of Tilapia: Selective Breeding for Cold Tolerance and for Growth Rate in Fresh and Saline Water. United States Department of Agriculture, November 2003. http://dx.doi.org/10.32747/2003.7586478.bard.

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The main objective of this project was to initiate a breeding program to produce cold-tolerant and salinity-tolerant synthetic breeds of tilapia, from a base population consisting of a four-species hybrid population created under an earlier BARD project. A secondary objective was to estimate genetic parameters for the traits growth rate under fresh- and salt-water and for cold tolerance. A third objective was to place quantitative trait loci that affect these traits of interest (e.g., growth rate in fresh-water, salt-water and cold tolerance) on the growing linkage map of primarily microsatellite loci. We have encountered fertility problems that were apparently the result of the complex genetic structure of this base population. The failure in producing the first generation of the breeding program has forced us to stop the intended breeding program. Thus, upon approval of BARD office, this objective was dropped and during the last year we have focused on the secondary objective of the original project during the third year of the project, but failed to perform the intended analysis to estimate genetic parameters for the traits of interest. We have succeeded, however, to strengthen the earlier identification of a QTL for cold tolerance by analyzing further segregating families. The results support the existence of a QTL for cold tolerance on linkage group 15, corresponding to UNH linkage group 23. The results also indicate a QTL for the same trait on linkage group 12, corresponding to UNH linkage group 4.
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Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.

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The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.
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Jung, Carina, Karl Indest, Matthew Carr, Richard Lance, Lyndsay Carrigee, and Kayla Clark. Properties and detectability of rogue synthetic biology (SynBio) products in complex matrices. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45345.

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Synthetic biology (SynBio) aims to rationally engineer or modify traits of an organism or integrate the behaviors of multiple organisms into a singular functional organism through advanced genetic engineering techniques. One objective of this research was to determine the environmental persistence of engineered DNA in the environment. To accomplish this goal, the environmental persistence of legacy engineered DNA building blocks were targeted that laid the foundation for SynBio product development and application giving rise to “post-use products.” These building blocks include genetic constructs such as cloning and expression vectors, promoter/terminator elements, selectable markers, reporter genes, and multi-cloning sites. Shotgun sequencing of total DNA from water samples of pristine sites was performed and resultant sequence data mined for frequency of legacy recombinant DNA signatures. Another objective was to understand the fate of a standardized contemporary synthetic genetic construct (SC) in the context of various chassis systems/genetic configurations representing different degrees of “genetic bioavailability” to the environmental landscape. These studies were carried out using microcosms representing different environmental matrices (soils, waters, wastewater treatment plant (WWTP) liquor) and employed a novel genetic reporter system based on volatile organic compounds (VOC) detection to assess proliferation and persistence of the SC in the matrix over time.
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Lamont, Susan J., E. Dan Heller, and Avigdor Cahaner. Prediction of Immunocompetence and Resistance to Disease by Using Molecular Markers of the Major Histocompatibility Complex. United States Department of Agriculture, September 1994. http://dx.doi.org/10.32747/1994.7568780.bard.

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This project utilized two live-animal populations in an integrated research program to identify molecular markers for immune response and disease resistance. The populations each had their foundation from meat-type commercial breeder chicken lines of their respective countries. Investigations effectively used unique availability of resources in each country to study commercial-type environments in Israel and line-crosses with diverse inbred lines in the US. Two bacterial systems were investigated to cover both respiratory and gastrointestinal, and primary and secondary, infections. Individual experimental groups of animals were evaluated for combinations of vaccine antibody levels, response to pathogen challenge, growth parameters, genetic background and molecular markers. The positive association of antibody level with resistance to disease was confirmed. Effectiveness of genetic selection for vaccine antibody response level was demonstrated. Molecular markers, both inside and outside the MHC region, were associated with antibody response and resistance to disease. Markers were shown to have a generalized effect, by association with multiple traits of immune response and disease resistance. The impact of genetic background on marker effect was shown to be important. The overall results demonstrate the effectiveness of selection on vaccine antibody response and the potential of molecular marker-assisted selection to improve efficiency of production of meat-type chickens by reducing genetic susceptibility to disease.
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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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Feldman, Moshe, Eitan Millet, Calvin O. Qualset, and Patrick E. McGuire. Mapping and Tagging by DNA Markers of Wild Emmer Alleles that Improve Quantitative Traits in Common Wheat. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7573081.bard.

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The general goal was to identify, map, and tag, with DNA markers, segments of chromosomes of a wild species (wild emmer wheat, the progenitor of cultivated wheat) determining the number, chromosomal locations, interactions, and effects of genes that control quantitative traits when transferred to a cultivated plant (bread wheat). Slight modifications were introduced and not all objectives could be completed within the human and financial resources available, as noted with the specific objectives listed below: 1. To identify the genetic contribution of each of the available wild emmer chromosome-arm substitution lines (CASLs) in the bread wheat cultivar Bethlehem for quantitative traits, including grain yield and its components and grain protein concentration and yield, and the effect of major loci affecting the quality of end-use products. [The quality of end-use products was not analyzed.] 2. To determine the extent and nature of genetic interactions (epistatic effects) between and within homoeologous groups 1 and 7 for the chromosome arms carrying "wild" and "cultivated" alleles as expressed in grain and protein yields and other quantitative traits. [Two experiments were successful, grain protein concentration could not be measured; data are partially analyzed.] 3. To derive recombinant substitution lines (RSLs) for the chromosome arms of homoeologous groups 1 and 7 that were found previously to promote grain and protein yields of cultivated wheat. [The selection of groups 1 and 7 tons based on grain yield in pot experiments. After project began, it was decided also to derive RSLs for the available arms of homoeologous group 4 (4AS and 4BL), based on the apparent importance of chromosome group 4, based on early field trials of the CASLs.] 4. To characterize the RSLs for quantitative traits as in objective 1 and map and tag chromosome segments producing significant effects (quantitative trait loci, QTLs by RFLP markers. [Producing a large population of RSLs for each chromosome arm and mapping them proved more difficult than anticipated, low numbers of RSLs were obtained for two of the chromosome arms.] 5. To construct recombination genetic maps of chromosomes of homoeologous groups 1 and 7 and to compare them to existing maps of wheat and other cereals [Genetic maps are not complete for homoeologous groups 4 and 7.] The rationale for this project is that wild species have characteristics that would be valuable if transferred to a crop plant. We demonstrated the sequence of chromosome manipulations and genetic tests needed to confirm this potential value and enhance transfer. This research has shown that a wild tetraploid species harbors genetic variability for quantitative traits that is interactive and not simply additive when introduced into a common genetic background. Chromosomal segments from several chromosome arms improve yield and protein in wheat but their effect is presumably enhanced when combination of genes from several segments are integrated into a single genotype in order to achieve the benefits of genes from the wild species. The interaction between these genes and those in the recipient species must be accounted for. The results of this study provide a scientific basis for some of the disappointing results that have historically obtained when using wild species as donors for crop improvement and provide a strategy for further successes.
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Fridman, Eyal, and Eran Pichersky. Tomato Natural Insecticides: Elucidation of the Complex Pathway of Methylketone Biosynthesis. United States Department of Agriculture, December 2009. http://dx.doi.org/10.32747/2009.7696543.bard.

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Plant species synthesize a multitude of specialized compounds 10 help ward off pests. and these in turn may well serve as an alternative to synthetic pesticides to reduce environmental damage and health risks to humans. The general goal of this research was to perform a genetic and biochemical dissection of the natural-insecticides methylketone pathway that is specific to the glandular trichomes of the wild species of tomato, Solanumhabrochaites f. glabratum (accession PI126449). Previous study conducted by us have demonstrated that these compounds are synthesized de novo as a derivate pathway of the fatty acid biosynthesis, and that a key enzyme. designated MethylketoneSynthase 1 (MKS 1). catalyzes conversion of the intermediate B-ketoacyl- ACPs to the corresponding Cn-1 methylketones. The approach taken in this proposed project was to use an interspecific F2 population. derived from the cross between the cultivated lV182 and the wild species PIl26449. for three objectives: (i) Analyze the association between allelic status of candidate genes from the fatty acid biosynthesis pathway with the methylketone content in the leaves (ii) Perform bulk segregant analysis of genetic markers along the tomato genome for identifying genomic regions that harbor QTLs for 2TD content (iii) Apply differential gene expression analysis using the isolated glands of bulk segregant for identifying new genes that are involved in the pathway. The genetic mapping in the interspecific F2 population included app. 60 genetic markers, including the candidate genes from the FAS pathway and SSR markers spread evenly across the genome. This initial; screening identified 5 loci associated with MK content including the candidate genes MKS1, ACC and MaCoA:ACP trans. Interesting observation in this genetic analysis was the connection between shape and content of the glands, i.e. the globularity of the four cells, typical to the wild species. was associated with increased MK in the segregating population. In the next step of the research transcriptomic analysis of trichomes from high- and 10w-MK plants was conducted. This analysis identified a new gene, Methy1ketone synthase 2 (MKS2), whose protein product share sequence similarity to the thioesterase super family of hot-dog enzymes. Genetic analysis in the segregating population confirmed its association with MK content, as well as its overexpression in E. coli that led to formation of MK in the media. There are several conclusions drawn from this research project: (i) the genetic control of MK accumulation in the trichomes is composed of biochemical components in the FAS pathway and its vicinity (MKS 1 and MKS2). as well as genetic factors that mediate the morphology of these specialized cells. (ii) the biochemical pathway is now realized different from what was hypothesized before with MKS2 working upstream to I\1KS 1 and serves as the interface between primary (fatty acids) and secondary (MK) metabolism. We are currently testing the possible physical interactions between these two proteins in vitro after the genetic analysis showed clear epistatic interactions. (iii) the regulation of the pathway that lead to specialized metabolism in the wild species is largely mediated by transcription and one of the achievements of this project is that we were able to isolate and verify the specificity of the MKS1 promoter to the trichomes which allows manipulation of the pathways in these cells (currently in progress). The scientific implications of this research project is the advancement in our knowledge of hitherto unknown biochemical pathway in plants and new leads for studying a new family in plants (hot dog thioesterase). The agricultural and biotechnological implication are : (i) generation of new genetic markers that could assist in importing this pathway to cultivated tomato hence enhancing its natural resistance to insecticides, (ii) the discovery of MKS2 adds a new gene for genetic engineering of plants for making new fatty acid derived compounds. This could be assisted with the use of the isolated and verified MKS1 promoter. The results of this research were summarized to a manuscript that was published in Plant Physiology (cover paper). to a chapter in a proceeding book. and one patent was submitted in the US.
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Weller, Joel I., Ignacy Misztal, and Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, March 2015. http://dx.doi.org/10.32747/2015.7594404.bard.

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The main objectives of this research was to detect the specific polymorphisms responsible for observed quantitative trait loci and develop optimal strategies for genomic evaluations and selection for moderate (Israel) and large (US) dairy cattle populations. A joint evaluation using all phenotypic, pedigree, and genomic data is the optimal strategy. The specific objectives were: 1) to apply strategies for determination of the causative polymorphisms based on the “a posteriori granddaughter design” (APGD), 2) to develop methods to derive unbiased estimates of gene effects derived from SNP chips analyses, 3) to derive optimal single-stage methods to estimate breeding values of animals based on marker, phenotypic and pedigree data, 4) to extend these methods to multi-trait genetic evaluations and 5) to evaluate the results of long-term genomic selection, as compared to traditional selection. Nearly all of these objectives were met. The major achievements were: The APGD and the modified granddaughter designs were applied to the US Holstein population, and regions harboring segregating quantitative trait loci (QTL) were identified for all economic traits of interest. The APGD was able to find segregating QTL for all the economic traits analyzed, and confidence intervals for QTL location ranged from ~5 to 35 million base pairs. Genomic estimated breeding values (GEBV) for milk production traits in the Israeli Holstein population were computed by the single-step method and compared to results for the two-step method. The single-step method was extended to derive GEBV for multi-parity evaluation. Long-term analysis of genomic selection demonstrated that inclusion of pedigree data from previous generations may result in less accurate GEBV. Major conclusions are: Predictions using single-step genomic best linear unbiased prediction (GBLUP) were the least biased, and that method appears to be the best tool for genomic evaluation of a small population, as it automatically accounts for parental index and allows for inclusion of female genomic information without additional steps. None of the methods applied to the Israeli Holstein population were able to derive GEBV for young bulls that were significantly better than parent averages. Thus we confirm previous studies that the main limiting factor for the accuracy of GEBV is the number of bulls with genotypes and progeny tests. Although 36 of the grandsires included in the APGD were genotyped for the BovineHDBeadChip, which includes 777,000 SNPs, we were not able to determine the causative polymorphism for any of the detected QTL. The number of valid unique markers on the BovineHDBeadChip is not sufficient for a reasonable probability to find the causative polymorphisms. Complete resequencing of the genome of approximately 50 bulls will be required, but this could not be accomplished within the framework of the current project due to funding constraints. Inclusion of pedigree data from older generations in the derivation of GEBV may result is less accurate evaluations.
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Ohad, Nir, and Robert Fischer. Regulation of plant development by polycomb group proteins. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7695858.bard.

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Our genetic and molecular studies have indicated that FIE a WD-repeat Polycomb group (PcG) protein takes part in multi-component protein complexes. We have shown that FIE PcG protein represses inappropriate programs of development during the reproductive and vegetative phases of the Arabidopsis life cycle. Moreover, we have shown that FIE represses the expression of key regulatory genes that promote flowering (AG and LFY), embryogenesis (LEC1), and shoot formation (KNAT1). These results suggest that the FIE PcG protein participates in the formation of distinct PcG complexes that repress inappropriate gene expression at different stages of plant development. PcG complexes modulate chromatin compactness by modifying histones and thereby regulate gene expression and imprinting. The main goals of our original project were to elucidate the biological functions of PcG proteins, and to understand the molecular mechanisms used by FIE PcG complexes to repress the expression of its gene targets. Our results show that the PcG complex acts within the central cell of the female gametophyte to maintain silencing of MEA paternal allele. Further more we uncovered a novel example of self-imprinting mechanism by the PgG complex. Based on results obtained in the cures of our research program we extended our proposed goals and elucidated the role of DME in regulating plant gene imprinting. We discovered that in addition to MEA,DME also imprints two other genes, FWA and FIS2. Activation of FWA and FIS2 coincides with a reduction in 5-methylcytosine in their respective promoters. Since endosperm is a terminally differentiated tissue, the methylation status in the FWA and FIS2 promoters does not need to be reestablished in the following generation. We proposed a “One-Way Control” model to highlight differences between plant and animal genomic imprinting. Thus we conclude that DEMETER is a master regulator of plant gene imprinting. Future studies of DME function will elucidate its role in processes and disease where DNA methylation has a key regulatory role both in plants and animals. Such information will provide valuable insight into developing novel strategies to control and improve agricultural traits and overcome particular human diseases.
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