Literatura académica sobre el tema "Quantitative genetics"

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Artículos de revistas sobre el tema "Quantitative genetics"

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Mackay, Trudy F. C., Michael Lynch, and Bruce Walsh. "Quantitative Genetics." Evolution 53, no. 1 (1999): 307. http://dx.doi.org/10.2307/2640946.

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Gunter, Chris. "Quantitative genetics." Nature 456, no. 7223 (2008): 719. http://dx.doi.org/10.1038/456719a.

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Mackay, Trudy F. C. "QUANTITATIVE GENETICS." Evolution 53, no. 1 (1999): 307–9. http://dx.doi.org/10.1111/j.1558-5646.1999.tb05359.x.

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Hill, William G. "Sewall Wright and quantitative genetics." Genome 31, no. 1 (1989): 190–95. http://dx.doi.org/10.1139/g89-033.

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Some aspects of Wright's great contribution to quantitative genetics and animal breeding are reviewed in relation to current research and practice. Particular aspects discussed are as follows: the utility of his definition of inbreeding coefficient in terms of the correlation of uniting gametes; the maintenance of genetic variation in the optimum model; the inter-relations between past and present animal-breeding practice and the shifting-balance theory of evolution.Key words: quantitative genetics, inbreeding coefficient, genetic variation, evolution.
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van Buijtenen, J. P. "Genomics and quantitative genetics." Canadian Journal of Forest Research 31, no. 4 (2001): 617–22. http://dx.doi.org/10.1139/x00-171.

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The interaction between genomics and quantitative genetics has been a two-way street. Genomics contributed genetic markers and genetic maps making it possible to study quantitative trait loci (QTLs), and quantitative genetics contributed new theories and computational techniques to deal with the data generated by QTL studies. QTL studies in forest trees have led to the discovery of a few major genes masquerading as quantitative genes, such as genes for rust resistance in several pine species. QTLs for many traits including height growth, leaf traits, wood specific gravity, flowering, frost res
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FRANKHAM, RICHARD. "Quantitative genetics in conservation biology." Genetical Research 74, no. 3 (1999): 237–44. http://dx.doi.org/10.1017/s001667239900405x.

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Most of the major genetic concerns in conservation biology, including inbreeding depression, loss of evolutionary potential, genetic adaptation to captivity and outbreeding depression, involve quantitative genetics. Small population size leads to inbreeding and loss of genetic diversity and so increases extinction risk. Captive populations of endangered species are managed to maximize the retention of genetic diversity by minimizing kinship, with subsidiary efforts to minimize inbreeding. There is growing evidence that genetic adaptation to captivity is a major issue in the genetic management
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Plomin, Robert, and Jenae Neiderhiser. "Quantitative Genetics, Molecular Genetics, and Intelligence." Intelligence 15, no. 4 (1991): 369–87. http://dx.doi.org/10.1016/0160-2896(91)90001-t.

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Hansen, Thomas F., and Christophe Pélabon. "Evolvability: A Quantitative-Genetics Perspective." Annual Review of Ecology, Evolution, and Systematics 52, no. 1 (2021): 153–75. http://dx.doi.org/10.1146/annurev-ecolsys-011121-021241.

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The concept of evolvability emerged in the early 1990s and soon became fashionable as a label for different streams of research in evolutionary biology. In evolutionary quantitative genetics, evolvability is defined as the ability of a population to respond to directional selection. This differs from other fields by treating evolvability as a property of populations rather than organisms or lineages and in being focused on quantification and short-term prediction rather than on macroevolution. While the term evolvability is new to quantitative genetics, many of the associated ideas and researc
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Macgregor, Stuart, Sara A. Knott, Ian White, and Peter M. Visscher. "Quantitative Trait Locus Analysis of Longitudinal Quantitative Trait Data in Complex Pedigrees." Genetics 171, no. 3 (2005): 1365–76. http://dx.doi.org/10.1534/genetics.105.043828.

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Slatkin, Montgomery. "Quantitative Genetics of Heterochrony." Evolution 41, no. 4 (1987): 799. http://dx.doi.org/10.2307/2408889.

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Tesis sobre el tema "Quantitative genetics"

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Olsson, Charlotta. "Quantitative analysis of disease associated mutations and sequence variants." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis : Univ.-bibl. [distributör], 2001. http://publications.uu.se/theses/91-554-5018-0/.

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Souleman, Dima. "Genetic consequences of colonization of a metal-polluted environment, population genetics and quantitative genetics approaches." Thesis, Lille 1, 2017. http://www.theses.fr/2017LIL10006/document.

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Les habitats naturels sont de plus en plus détruits et fragmentés par l'expansion urbaine et les activités humaines. La fragmentation des espaces naturels et agricoles par les bâtiments et les nouvelles infrastructures affecte la taille, la connectivité et la qualité des habitats. Les populations d’organismes vivants sur ces territoires anthropisés sont alors plus isolées. Or, la différenciation entre populations d’un même organisme dépend de processus démographiques et génétiques tels que la dérive génétique, le flux génétique, la mutation et la sélection naturelle. La persistance et le dével
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Santure, Anna Wensley, and n/a. "Quantitative genetic models for genomic imprinting." University of Otago. Department of Zoology, 2006. http://adt.otago.ac.nz./public/adt-NZDU20060811.134008.

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A gene is imprinted when its expression is dependent on the sex of the parent from which it was inherited. An increasing number of studies are suggesting that imprinted genes have a major influence on medically, agriculturally and evolutionarily important traits, such as disease severity and livestock production traits. While some genes have a large effect on the traits of an individual, quantitative characters such as height are influenced by many genes and by the environment, including maternal effects. The interaction between these genes and the environment produces variation in the charact
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Shen, Xia. "Novel Statistical Methods in Quantitative Genetics : Modeling Genetic Variance for Quantitative Trait Loci Mapping and Genomic Evaluation." Doctoral thesis, Uppsala universitet, Beräknings- och systembiologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-170091.

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This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL m
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Keightley, Peter D. "Studies of quantitative genetic variation." Thesis, University of Edinburgh, 1988. http://hdl.handle.net/1842/12340.

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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
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Cerqueira, Pedro Henrique Ramos. "Structural equation models applied to quantitative genetics." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-05112015-145419/.

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Causal models have been used in different areas of knowledge in order to comprehend the causal associations between variables. Over the past decades, the amount of studies using these models have been growing a lot, especially those related to biological systems where studying and learning causal relationships among traits are essential for predicting the consequences of interventions in such system. Graph analysis (GA) and structural equation modeling (SEM) are tools used to explore such associations. While GA allows searching causal structures that express qualitatively how variables are cau
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Mayo, Oliver. "Contributions to quantitative and population genetics : a collection of publications with introduction." Title page, contents and introduction only, 1987. http://web4.library.adelaide.edu.au/theses/09SD/09sdm473.pdf.

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Title from container. Includes bibliographies and indexes. Contributions to quantitative and population genetics -- The biochemical genetics of man -- The theory of plant breeding -- Natural selection and its constraints.
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Randall, Joshua Charles. "Large-scale genetic analysis of quantitative traits." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:addfb69d-602c-43e3-ab18-6e6d3b269076.

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Recent advances in genotyping technology coupled with an improved understanding of the architecture of linkage disequilibrium across the human genome have resulted in genome-wide association studies (GWAS) becoming a useful and widely applied tool for discovering common genetic variants associated with both quantitative traits and disease risk. After each GWAS was completed, it left behind a set of genotypes and phenotypes, often including anthropometric measures used as covariates. Genetic associations with anthropometric measures are not well characterized, perhaps due to lack of power to de
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Wambach, Tina. "Effects of epistatic interaction on detection and parameter analysis of quantitative trait loci." Thesis, McGill University, 2001. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=33039.

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Recent scientific support for the involvement of genetic locus interaction in quantitative trait variation and the widespread use of quantitative trait locus (QTL) mapping has resulted in the need to examine those aspects concurrently. Computer software was written to simulate interacting quantitative trait loci (QTLs) in plant populations. Using this software, interacting QTLs were simulated to examine effects of epistasis on the detection of QTLs and the quality of QTL parameter estimates. Simulations involved doubled haploid populations exhibiting two non-epistatic traits and seven epistati
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Libros sobre el tema "Quantitative genetics"

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Xu, Shizhong. Quantitative Genetics. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6.

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Falconer, D. S. Introductionto quantitative genetics. 3rd ed. Longman Scientific & Technical, 1989.

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Roff, Derek A. Evolutionary Quantitative Genetics. Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-4080-9.

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C, MacKay Trudy F., ed. Introduction to quantitative genetics. 4th ed. Prentice Hall, 1996.

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Hallauer, Arnel R. Quantitative genetics in maize breeding. 3rd ed. Springer, 2010.

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Hallauer, Arnel R. Quantitative genetics in maize breeding. 3rd ed. Springer, 2010.

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Falconer, D. S. Introduction to quantitative genetics. 3rd ed. Longman Scientific & Technical, 1989.

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Becker, Walter A. Manual of quantitative genetics. 5th ed. Academic Enterprises, 1992.

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Falconer, D. S. Introduction to quantitative genetics. 3rd ed. Longman, Scientific & Technical, 1989.

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Falconer, D. S. Introduction to quantitative genetics. 2nd ed. Longman Scientific & Technical, 1986.

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Capítulos de libros sobre el tema "Quantitative genetics"

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Nagylaki, Thomas. "Quantitative Genetics." In Introduction to Theoretical Population Genetics. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-76214-7_10.

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Priyadarshan, P. M. "Quantitative Genetics." In PLANT BREEDING: Classical to Modern. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7095-3_14.

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Princée, F. P. G. "Quantitative Genetics." In Topics in Biodiversity and Conservation. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50032-4_16.

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Chatterjee, Anindo. "Quantitative Genetics." In Genetics Fundamentals Notes. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-7041-1_20.

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Laurentin Táriba, Hernán Eduardo. "Quantitative Genetics." In Agricultural Genetics. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37192-9_12.

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Kulandhasamy, Maheswari, Sunil Singh, and Indrani Mukherjee. "Quantitative Genetics." In Encyclopedia of Animal Cognition and Behavior. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-47829-6_168-1.

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Kulandhasamy, Maheswari, Sunil Singh, and Indrani Mukherjee. "Quantitative Genetics." In Encyclopedia of Animal Cognition and Behavior. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_168.

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Meredith, William R. "Quantitative Genetics." In Agronomy Monographs. American Society of Agronomy, Crop Science Society of America, Soil Science Society of America, 2016. http://dx.doi.org/10.2134/agronmonogr24.c5.

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Campbell, B. Todd, and Gerald O. Myers. "Quantitative Genetics." In Agronomy Monographs. American Society of Agronomy, Inc., Crop Science Society of America, Inc., and Soil Science Society of America, Inc., 2015. http://dx.doi.org/10.2134/agronmonogr57.2013.0024.

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Xu, Shizhong. "Resemblance between Relatives." In Quantitative Genetics. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6_9.

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Actas de conferencias sobre el tema "Quantitative genetics"

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Sun, Zhongle. "Quantitative Analysis Model of Multi-Objective Management in Engineering Projects Based on Genetic Algorithm." In 2024 Asia Pacific Conference on Innovation in Technology (APCIT). IEEE, 2024. http://dx.doi.org/10.1109/apcit62007.2024.10673614.

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Paladi, Dana, Eugenia Cotenco, and Iu Siromyatnikov. "Biomorphological and quantitative characteristics of tomato SC0 somaclones." In Scientific International Symposium “Advanced Biotechnologies - Achievements and Prospects” (VIth Edition). Institute of Genetics, Physiology and Plant Protection, 2022. http://dx.doi.org/10.53040/abap6.2022.108.

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With the development of cellular biology, molecular genetics, biochemistry, biophysics, microbiology and genetic engineering, artificially manipulating the genetic information of li-ving organisms became possible resulting in modern biotechnologies with special implications in the improvement of plants and animals, production of pharmaceutical and cosmetic ingre-dients, valuable chemical and bioenergetic products [1]. In vitro culture is a set of techniques that requires the use of aseptic elements and the creation of a perfectly controlled environment, being an advantageous way to increase the
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Galas, David, James Kunert-Graf, and Nikita Sakhanenko. "Developing an information theory of quantitative genetics." In Entropy 2021: The Scientific Tool of the 21st Century. MDPI, 2021. http://dx.doi.org/10.3390/entropy2021-09821.

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Santana, Roberto, Hossein Karshenas, Concha Bielza, and Pedro Larrañaga. "Quantitative genetics in multi-objective optimization algorithms." In the 13th annual conference companion. ACM Press, 2011. http://dx.doi.org/10.1145/2001858.2001911.

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Milkevych, V., E. Karaman, G. Sahana, L. Janss, Z. Cai, and M. S. Lund. "351. Quantitative trait simulation using MeSCoT software." In World Congress on Genetics Applied to Livestock Production. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_351.

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"Quantitative real-time PCR as a supplementary tool for molecular cytogenetics." 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/plantgen2019-044.

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Bijma, P., A. D. Hulst, and M. C. M. de Jong. "163. A quantitative genetic theory for infectious diseases." In World Congress on Genetics Applied to Livestock Production. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_163.

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Davoodi, P., A. Ehsani, R. Vaez Torshizi, and A. A. Masoudi. "596. Chicken quantitative traits follow the omnigenic model." In World Congress on Genetics Applied to Livestock Production. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_596.

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"Methods of computer vision to extract the quantitative characteristics of the wheat spike." 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/plantgen2019-060.

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Tsuruta, S., D. A. L. Lourenco, and I. Misztal. "432. Efficient genetic progress for quantitative traits through genomic selection." In World Congress on Genetics Applied to Livestock Production. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_432.

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Informes sobre el tema "Quantitative genetics"

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Paran, Ilan, and Molly Jahn. Genetics and comparative molecular mapping of biochemical and morphological fruit characters in Capsicum. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7586545.bard.

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Original objectives: The overall goal of our work was to gain information regarding the genetic and molecular control of pathways leading to the production of secondary metabolites determining major fruit quality traits in pepper and to develop tools based on this information to assist in crop improvement. The specific objectives were to: (1) Generate a molecular map of pepper based on simple sequence repeat (SSR) markers. (2) Map QTL for capsaicinoid (pungency) content (3) Determine possible association between capsaicinoid and carotenoid content and structural genes for capsaicinoid and caro
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Zhang, Hongbin B., David J. Bonfil, and Shahal Abbo. Genomics Tools for Legume Agronomic Gene Mapping and Cloning, and Genome Analysis: Chickpea as a Model. United States Department of Agriculture, 2003. http://dx.doi.org/10.32747/2003.7586464.bard.

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The goals of this project were to develop essential genomic tools for modern chickpea genetics and genomics research, map the genes and quantitative traits of importance to chickpea production and generate DNA markers that are well-suited for enhanced chickpea germplasm analysis and breeding. To achieve these research goals, we proposed the following research objectives in this period of the project: 1) Develop an ordered BAC library with an average insert size of 150 - 200 kb (USA); 2) Develop 300 simple sequence repeat (SSR) markers with an aid of the BAC library (USA); 3) Develop SSR marker
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Blum, Abraham, Henry T. Nguyen, and N. Y. Klueva. The Genetics of Heat Shock Proteins in Wheat in Relation to Heat Tolerance and Yield. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568105.bard.

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Fifty six diverse spring wheat cultivars were evaluated for genetic variation and heritability for thermotolerance in terms of cell-membrane stability (CMS) and triphenyl tetrazolium chloride (TTC) reduction. The most divergent cultivars for thermotolerance (Danbata-tolerant and Nacozari-susceptible) were crossed to develop an F8 random onbred line (RIL) population. This population was evaluated for co-segragation in CMS, yield under heat stress and HSP accumulation. Further studies of thermotolerance in relations to HSP and the expression of heterosis for growth under heat stress were perform
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Paran, Ilan, and Molly Jahn. Analysis of Quantitative Traits in Pepper Using Molecular Markers. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7570562.bard.

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Original objectives: The overall goal of the proposal was to determine the genetic and molecular control of pathways leading to the production of secondary metabolites determining major fruit quality traits in pepper. The specific objectives were to: (1) Generate a molecular map of pepper based on simple sequence repeat (SSR) markers. (2) Map QTL for capsaicinoids content (3) Determine possible association between capsaicinoids and carotenoid content and structural genes for capsaicinoid and carotenoid biosynthesis. (4) Map QTL for quantitative traits controlling additional fruit traits. (5) M
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Sherman, Amir, Rebecca Grumet, Ron Ophir, Nurit Katzir, and Yiqun Weng. Whole genome approach for genetic analysis in cucumber: Fruit size as a test case. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7594399.bard.

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The Cucurbitaceae family includes a broad array of economically and nutritionally important crop species that are consumed as vegetables, staple starches and desserts. Fruit of these species, and types within species, exhibit extensive diversity as evidenced by variation in size, shape, color, flavor, and others. Fruit size and shape are critical quality determinants that delineate uses and market classes and are key traits under selection in breeding programs. However, the underlying genetic bases for variation in fruit size remain to be determined. A few species the Cucurbitaceae family were
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Moore, Gloria A., Gozal Ben-Hayyim, Charles L. Guy, and Doron Holland. Mapping Quantitative Trait Loci in the Woody Perennial Plant Genus Citrus. United States Department of Agriculture, 1995. http://dx.doi.org/10.32747/1995.7570565.bard.

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As is true for all crops, production of Citrus fruit is limited by traits whose characteristics are the products of many genes (i.e. cold hardiness). In order to modify these traits by marker aided selection or molecular genetic techniques, it is first necessary to map the relevant genes. Mapping of quantitative trait loci (QTLs) in perennial plants has been extremely difficult, requiring large numbers of mature plants. Production of suitable mapping populations has been inhibited by aspects of reproductive biology (e.g. incompatibility, apomixis) and delayed by juvenility. New approaches prom
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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, 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 chromosom
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Orphan, Victoria, Gene Tyson, Christof Meile, et al. Systems Level Dissection of Anaerobic Methane Cycling: Quantitative Measurements of Single Cell Ecophysiology, Genetic Mechanisms, and Microbial Interactions. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1414771.

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Santa Sepúlveda, Juan David, Jhon Berdugo Cely, Mauricio Soto Suárez, Teresa Mosquera, and Carlos Galeano. A genetic linkage map of tetraploid potato (Solanum tuberosum L.) for Phytophthora infestans and Tecia solanivora quantitative resistance. Corporación Colombiana de Investigación Agropecuaria - AGROSAVIA, 2016. http://dx.doi.org/10.21930/agrosavia.poster.2016.28.

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Los avances en la selección asistida de selección molecular y marcadores han sido limitados debido a a los problemas de alta heterocigosis y ploidía en el grupo de papa Andigenum (adg). Recientemente, Se han desarrollado mapas basados ??en SNP de alta densidad para papa diploide y tetraploide. Además, los modelos estadísticos que incluyen la dosificación alélica, están mejorando la vinculación mapeo y análisis de QTL en papa autotetraploide (Hackett et al., 2014). Estos enfoques han facilitado el análisis de QTL de rasgos agronómicos como resistencia a P. infestans (Massa et al., 2015). La pro
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Weller, Joel I., Harris A. Lewin, and Micha Ron. Determination of Allele Frequencies for Quantitative Trait Loci in Commercial Animal Populations. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7586473.bard.

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Individual loci affecting economic traits in dairy cattle (ETL) have been detected via linkage to genetic markers by application of the granddaughter design in the US population and the daughter design in the Israeli population. From these analyses it is not possible to determine allelic frequencies in the population at large, or whether the same alleles are segregating in different families. We proposed to answer this question by application of the "modified granddaughter design", in which granddaughters with a common maternal grandsire are both genotyped and analyzed for the economic traits.
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