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 (February 1999): 307. http://dx.doi.org/10.2307/2640946.
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Gunter, Chris. "Quantitative genetics." Nature 456, no. 7223 (December 2008): 719. http://dx.doi.org/10.1038/456719a.
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Mackay, Trudy F. C. "QUANTITATIVE GENETICS." Evolution 53, no. 1 (February 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 (January 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 (April 1, 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 resistance, disease resistance, and ease of vegetative propagation were found in one or more species. Spring cold hardiness in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) holds the record for number of QTLs with 14. Generally the number is under seven. The effects are often large, but this may often be due to small population sizes. At this time the impact on forest tree breeding is small, although the potential is certainly there. An interesting marker aided back-crossing program is underway in American chestnut (Castanea dentata (Marsh.) Borkh.).
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FRANKHAM, RICHARD. "Quantitative genetics in conservation biology." Genetical Research 74, no. 3 (December 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 of captive populations of endangered species as it reduces reproductive fitness when captive populations are reintroduced into the wild. This problem is not currently addressed, but it can be alleviated by deliberately fragmenting captive populations, with occasional exchange of immigrants to avoid excessive inbreeding. The extent and importance of outbreeding depression is a matter of controversy. Currently, an extremely cautious approach is taken to mixing populations. However, this cannot continue if fragmented populations are to be adequately managed to minimize extinctions. Most genetic management recommendations for endangered species arise directly, or indirectly, from quantitative genetic considerations.
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Plomin, Robert, and Jenae Neiderhiser. "Quantitative Genetics, Molecular Genetics, and Intelligence." Intelligence 15, no. 4 (October 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 (November 2, 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 research questions have been with the field from its inception as biometry. Recent research on evolvability is more than a relabeling of old questions, however. New operational measures of evolvability have opened possibilities for understanding adaptation to rapid environmental change, assessing genetic constraints, and linking micro- and macroevolution.
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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 (July 14, 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 (July 1987): 799. http://dx.doi.org/10.2307/2408889.
Texto completoTesis 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 développement des populations dans des conditions environnementales modifiées dépendent de mécanismes de tolérance. Dans ce contexte, l'introduction de contaminants tels que des métaux dans l'environnement peut influencer l'évolution des plantes et des animaux en modifiant les forces évolutives et en créant des différences entre populations. Dans ce travail, l’attention a été portée sur les conséquences génétiques de la pollution métallique sur deux espèces, le ver de terre Lumbricus terrestris et une plante modèle Arabidopsis halleri. Deux approches différentes ont été utilisées pour étudier la réponse génétique à la contamination métallique : une approche de génétique des populations chez L. terrestris et une approche de génétique quantitative chez A. halleri. Tout d’abord, il s’est agi d’identifier et de valider de nouveaux marqueurs microsatellites chez L. terrestris. Ensuite, ces marqueurs ont été utilisés afin de caractériser la diversité génétique neutre chez des vers collectés sur des sites agricoles et urbanisés. Parallèlement, l'architecture génétique de la tolérance et de l'hyperaccumulation de Zn chez A. halleri a été explorée à l’aide d’un croisement intraspécifique entre une population métallicole et une population non métallicole. Une densité élevée de marqueurs SNP a été utilisée pour procéder à l'étape de cartographie QTL<br>Natural habitats are more and more destructed and fragmented by urban expansion and human activities. The fragmentation of natural and agricultural areas by buildings and new infrastructures affects the size, connectivity and the quality of habitats. The populations of organisms inhabiting these anthropized territories are then more isolated. However, differentiation between populations of the same organism depends on demographic and genetic processes such as genetic drift, gene flow, mutation and natural selection. Only species that have developed special tolerance mechanisms can persist under changed environmental conditions. The introduction of contaminants such as metals in the environment may influence plants and animals evolution by modifying the evolutionary forces and thus generating differences between populations. In this work, attention was focused on the genetic consequences of metallic pollution on two species, the earthworm Lumbricus terrestris and the plant model Arabidopsis halleri. Two different approaches have been used to study the genetic response to metallic contamination: a population genetic approach was performed in L. terrestris and a quantitative genetic approach was carried on in A. halleri. First, it was a question of identifying and validating new microsatellite markers in L. terrestris. These markers were then used to characterize the neutral genetic diversity in worms collected from agricultural and urban sites. Secondly, genetic architecture of Zn tolerance and Zn hyperaccumulation was conducted investigated for the first time using an intraspecific crossing between metallicolous and non-metallicolous individuals of A. halleri. High density of SNP markers was used to proceed to the QTL mapping step
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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 characteristics of individuals. Many quantitative characters are likely to be influenced by a small number of imprinted genes, but at present there is no general theoretical model of the quantitative genetics of imprinting incorporating multiple loci, environmental effects and maternal effects. This research develops models for the quantitative genetics of imprinting incorporating these effects, including deriving expressions for genetic variation and resemblances between relatives. Imprinting introduces both parent-of-origin and generation dependent differences in the derivation of standard quantitative genetic models that are generally equivalent under Mendelian expression. Further, factors such as epistasis, maternal effects and interactions between genotype and environment may mask the effect of imprinting in a quantitative trait. Maternal effects may also mimic a number of signatures in variance and covariance components that are expected in a population with genomic imprinting. This research allows a more comprehensive understanding of the processes influencing an individual�s characteristics.
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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 mapping in terms of precision. Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes. The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).
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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 & Environmental Science UNSW. "The use of microsatellites as a surrogate for quantitative trait variation in conservation." Awarded by:University of New South Wales. School of Biological, Earth and Environmental Science, 2003. http://handle.unsw.edu.au/1959.4/22457.
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Conservation biologists are interested in maintaining genetic variation in small populations, with a view to maintaining fitness and the ability of the species to adapt to changing environmental conditions. The most important type of genetic variation is therefore that which affects fitness and reproduction, and is therefore subject to natural selection. Such fitness traits are often quantitative, i.e. are the result of a suite of loci, and are continuously variable. Microsatellite markers are a popular method of determining the level of variation present in a species??? genome. The assumption is made that microsatellites, which are neutral markers, behave in the same manner as quantitative traits. If this assumption were proved incorrect, then the use of neutral markers in conservation monitoring would have to be re-evaluated. In this study, experiments have been conducted using Drosophila melanogaster to test the assumption that variation in quantitative traits under stabilising selection declines at the same rate as heterozygosity in microsatellite markers, during a population bottleneck. Experimental population bottlenecks were of two effective population sizes (Ne), Ne=2 for one generation and Ne=60 for 35 generations. Based on the effective population size, we expected both types of bottlenecks to lose 25% of neutral genetic variation. Ten replicates of each bottleneck were maintained, along with four large control populations with Ne=320. In each population, heterozygosity (He) for eight microsatellite loci was compared with the heritability and additive genetic variance of two quantitative traits subject to balancing selection: fecundity and sternopleural bristle number. Microsatellite heterozygosity decreased in accordance with neutral predictions, whereas additive genetic variation in quantitative traits altered more than expected in both large and in bottlenecked populations relative to the initial sampling values, indicating that variation in quantitative traits was not being lost at the same rate as predicted by neutral theory. For most traits, the changes in additive genetic variance were congruent in all populations, large or bottlenecked. This congruence suggests that a common process was affecting all populations, such as adaptation. A mite infestation in early generations is a possible source of selective pressure. When bottlenecked populations were compared to the contemporaneous large populations (Ne = 320), the additive genetic variance of most traits was seen to have been lost in accordance with predictions from the loss of microsatellite heterozygosity. Loss of variation in microsatellites can thus be used to predict the loss of variation in quantitative traits due to bottlenecks, but not to predict the potentially much larger changes due to other processes such as adaptation. The effects of concurrent environmental stress and reduced population size were also evaluated. Endangered populations are often subject to environmental stress in addition to reduced population size, but the effect of stress on the additive genetic variance of fitness traits in organisms undergoing population bottlenecks is unknown. If the presence of stress alters the level of additive genetic variance in fitness traits, the viability of such populations could be substantially affected. The loss of microsatellite heterozygosity was not affected by the presence of a stress agent during a bottleneck. I found some significant effects of stress on the additive genetic variance of sternopleural bristles and fecundity; there was also a significant interaction between stress and the response to directional selection in sternopleural bristles. There was also an increase in the coefficient of variation of VA for sternopleural bristles. Stress may therefore affect the manner in which populations respond to selective pressures.
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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 causally connected, fitting SEM with a known causal structure allows to infer the magnitude of causal effects. Also SEM can be viewed as multiple regression models in which response variables can be explanatory variables for others. In quantitative genetics studies, SEM aimed to study the direct and indirect genetic effects associated to individuals through information related to them, beyond the observed characteristics, such as the kinship relations. In those studies typically the assumptions of linear relationships among traits are made. However, in some scenarios, nonlinear relationships can be observed, which make unsuitable the mentioned assumptions. To overcome this limitation, this paper proposes to use a mixed effects polynomial structural equation model, second or superior degree, to model those nonlinear relationships. Two studies were developed, a simulation and an application to real data. The first study involved simulation of 50 data sets, with a fully recursive causal structure involving three characteristics in which linear and nonlinear causal relations between them were allowed. The second study involved the analysis of traits related to dairy cows of the Holstein breed. Phenotypic relationships between traits were calving difficulty, gestation length and also the proportion of perionatal death. We compare the model of multiple traits and polynomials structural equations models, under different polynomials degrees in order to assess the benefits of the SEM polynomial of second or higher degree. For some situations the inappropriate assumption of linearity results in poor predictions of the direct, indirect and total of the genetic variances and covariance, either overestimating, underestimating, or even assign opposite signs to covariances. Therefore, we conclude that the inclusion of a polynomial degree increases the SEM expressive power.<br>Modelos causais têm sido muitos utilizados em estudos em diferentes áreas de conhecimento, a fim de compreender as associações ou relações causais entre variáveis. Durante as últimas décadas, o uso desses modelos têm crescido muito, especialmente estudos relacionados à sistemas biológicos, uma vez que compreender as relações entre características são essenciais para prever quais são as consequências de intervenções em tais sistemas. Análise do grafo (AG) e os modelos de equações estruturais (MEE) são utilizados como ferramentas para explorar essas relações. Enquanto AG nos permite buscar por estruturas causais, que representam qualitativamente como as variáveis são causalmente conectadas, ajustando o MEE com uma estrutura causal conhecida nos permite inferir a magnitude dos efeitos causais. Os MEE também podem ser vistos como modelos de regressão múltipla em que uma variável resposta pode ser vista como explanatória para uma outra característica. Estudos utilizando MEE em genética quantitativa visam estudar os efeitos genéticos diretos e indiretos associados aos indivíduos por meio de informações realcionadas aos indivíduas, além das característcas observadas, como por exemplo o parentesco entre eles. Neste contexto, é tipicamente adotada a suposição que as características observadas são relacionadas linearmente. No entanto, para alguns cenários, relações não lineares são observadas, o que torna as suposições mencionadas inadequadas. Para superar essa limitação, este trabalho propõe o uso de modelos de equações estruturais de efeitos polinomiais mistos, de segundo grau ou seperior, para modelar relações não lineares. Neste trabalho foram desenvolvidos dois estudos, um de simulação e uma aplicação a dados reais. O primeiro estudo envolveu a simulação de 50 conjuntos de dados, com uma estrutura causal completamente recursiva, envolvendo 3 características, em que foram permitidas relações causais lineares e não lineares entre as mesmas. O segundo estudo envolveu a análise de características relacionadas ao gado leiteiro da raça Holandesa, foram utilizadas relações entre os seguintes fenótipos: dificuldade de parto, duração da gestação e a proporção de morte perionatal. Nós comparamos o modelo misto de múltiplas características com os modelos de equações estruturais polinomiais, com diferentes graus polinomiais, a fim de verificar os benefícios do MEE polinomial de segundo grau ou superior. Para algumas situações a suposição inapropriada de linearidade resulta em previsões pobres das variâncias e covariâncias genéticas diretas, indiretas e totais, seja por superestimar, subestimar, ou mesmo atribuir sinais opostos as covariâncias. Portanto, verificamos que a inclusão de um grau de polinômio aumenta o poder de expressão do MEE.
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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 detect them in the sample sizes of individual studies. To improve power to detect variants associated with complex phenotypes such as anthropometric traits, data from multiple GWAS can be combined. This thesis describes the methods and results of several such analyses performed as part of the Genome-wide Investigation of ANThropemtric measures (GIANT) consortium, and compares various different methods that can be used to perform combined analyses of GWAS. In particular, the comparisons focus on comparing differences between meta-analysis methods, in which only summary statistics that result from within-study association testing are shared between studies, and mega-analysis methods in which individual-level genotype and phenotype data is analysed together. Finally, a brief discussion of technological means that have the potential to help overcome some of the challenges associated with performing mega-analyses is offered in order to suggest future work that could be undertaken in this area.
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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 epistatic traits, each trait at four levels of heritability. Detection efficiency of QTL main and interaction effects decreased with decreasing heritability. At a given level of broad-sense heritability, traits differed with respect to the relative quality of main-effect detection and interaction-effect detection. Main-effect detection was notably poor for one epistatic locus that has a relatively small additive effect. Position estimates were accurate but their precision deteriorated with decreasing heritability. The quality of QTL effect estimates declined consistently with decreasing heritability, and loss in the accuracy was associated with losses in power of detection.
Libros sobre el tema "Quantitative genetics"
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Xu, Shizhong. Quantitative Genetics. Cham: 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. Harlow: Longman Scientific & Technical, 1989.
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Roff, Derek A. Evolutionary Quantitative Genetics. Boston, MA: 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. Harlow: Prentice Hall, 1996.
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Hallauer, Arnel R. Quantitative genetics in maize breeding. 3rd ed. New York: Springer, 2010.
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Hallauer, Arnel R. Quantitative genetics in maize breeding. 3rd ed. New York: Springer, 2010.
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Falconer, D. S. Introduction to quantitative genetics. 3rd ed. London: Longman Scientific & Technical, 1989.
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Becker, Walter A. Manual of quantitative genetics. 5th ed. Pullman, WA, U.S.A: Academic Enterprises, 1992.
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Falconer, D. S. Introduction to quantitative genetics. 3rd ed. Burnt Mill, Harlow, Essex, England: Longman, Scientific & Technical, 1989.
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Falconer, D. S. Introduction to quantitative genetics. 2nd ed. Burnt Mill, Harlow, Essex, England: Longman Scientific & Technical, 1986.
Buscar texto completoCapítulos de libros sobre el tema "Quantitative genetics"
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Nagylaki, Thomas. "Quantitative Genetics." In Introduction to Theoretical Population Genetics, 279–339. Berlin, Heidelberg: 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, 269–98. Singapore: 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, 219–43. Cham: 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, 1029–76. Singapore: 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, 167–78. Cham: 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, 1–3. Cham: 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, 5837–39. Cham: 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, 131–50. Madison, WI, USA: 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, 187–203. Madison, WI, USA: 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, 135–46. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-83940-6_9.
Texto completoActas 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), 1–5. 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), 325–27. 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 chances of inducing and obtaining somaclonal ge-netic variability and stable genetic somaclones [2].
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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. Basel, Switzerland: 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. New York, New York, USA: 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. The Netherlands: 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. The Netherlands: 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. The Netherlands: 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. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_432.
Texto completoInformes 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, March 2005. http://dx.doi.org/10.32747/2005.7586545.bard.
Texto completoResumen
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 carotenoid biosynthesis. (4) Map QTL for quantitative traits controlling additional fruit traits. (5) Map fruit-specific ESTs and determine possible association with fruit QTL (6) Map the C locus that determines the presence and absence of capsaicinoid in pepper fruit and identify candidate genes for C.locus. Background: Pungency, color, fruit shape and fruit size are among the most important fruit quality characteristics of pepper. Despite the importance of the pepper crop both in the USA and Israel, the genetic basis of these traits was poorly understood prior to the studies conducted in the present proposal. In addition, molecular tools for use in pepper improvement were lacking. Major conclusions and achievements: Our studies enabled the development of a saturated genetic map of pepper that includes numerous SSR markers. This map has been integrated with a number of other independent maps resulting in the publication of a single resource map consisting of more than 2000 markers. Unlike previous maps based primarily on tomato-originated RFLP markers, the new maps are based on PCR markers that originate in Capsicum providing a comprehensive and versatile resource for marker-assisted selection in pepper. We determined the genetic and molecular bases of qualitative and quantitative variation of pungency, a character unique to pepper fruit. We mapped and subsequently cloned the Pun1 gene that serves as a master regulatoar for capsaicinoid accumulation and showed that it is an acyltransferase. By sequencing the Pun1 gene in pungent and non-pungent cultivars we identified a deletion that abolishes the expression of the gene in the latter cultivars. We also identified QTL that control capsaicinoid content and therefore pungency level. These genes will allow pepper breeders to manipulate the level of pungency for specific agricultural and industrial purposes. In addition to pungency we identified genes and QTL that control other key developmental processes of fruit development such as color, texture and fruit shape. The A gene controlling anthocyanin accumulation in the immature fruit was found as the ortholog of the petunia transcription factor Anthocyanin2. The S gene required for the soft flesh and deciduous fruit nature typical of wild peppers was identified as the ortholog of tomato polygalacturonase. We identified two major QTL controlling fruit shape, fs3.1 and fs10.1, that differentiate elongated and blocky and round fruit shapes, respectively. Scientific and agricultural implications: Our studies allowed significant advances in our understanding of important processes of pepper fruit development including the isolation and characterization of several well known genes. These results also provided the basis for the development of molecular tools that can be implemented for pepper improvement. A total of eleven refereed publications have resulted from this work, and several more are in preparation.
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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, March 2003. http://dx.doi.org/10.32747/2003.7586464.bard.
Texto completoResumen
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 tags for Ascochyta response, flowering date and grain weight (USA); 4) Develop a molecular genetic map consisting of at least 200 SSR markers (Israel and USA); 5) Map genes and QTLs most important to chickpea production in the U.S. and Israel: Ascochyta response, flowering and seed set date, grain weight, and grain yield under extreme dryland conditions (Israel); and 6) Determine the genetic correlation between the above four traits (Israel). Chickpea is the third most important pulse crop in the world and ranks the first in the Middle East. Chickpea seeds are a good source of plant protein (12.4-31.5%) and carbohydrates (52.4-70.9%). Although it has been demonstrated in other major crops that the modern genetics and genomics research is essential to enhance our capacity for crop genetic improvement and breeding, little work was pursued in these research areas for chickpea. It was absent in resources, tools and infrastructure that are essential for chickpea genomics and modern genetics research. For instance, there were no large-insert BAC and BIBAC libraries, no sufficient and user- friendly DNA markers, and no intraspecific genetic map. Grain sizes, flowering time and Ascochyta response are three main constraints to chickpea production in drylands. Combination of large seeds, early flowering time and Ascochyta blight resistance is desirable and of significance for further genetic improvement of chickpea. However, it was unknown how many genes and/or loci contribute to each of the traits and what correlations occur among them, making breeders difficult to combine these desirable traits. In this period of the project, we developed the resources, tools and infrastructure that are essential for chickpea genomics and modern genetics research. In particular, we constructed the proposed large-insert BAC library and an additional plant-transformation-competent BIBAC library from an Israeli advanced chickpea cultivar, Hadas. The BAC library contains 30,720 clones and has an average insert size of 151 kb, equivalent to 6.3 x chickpea haploid genomes. The BIBAC library contains 18,432 clones and has an average insert size of 135 kb, equivalent to 3.4 x chickpea haploid genomes. The combined libraries contain 49,152 clones, equivalent to 10.7 x chickpea haploid genomes. We identified all SSR loci-containing clones from the chickpea BAC library, generated sequences for 536 SSR loci from a part of the SSR-containing BACs and developed 310 new SSR markers. From the new SSR markers and selected existing SSR markers, we developed a SSR marker-based molecular genetic map of the chickpea genome. The BAC and BIBAC libraries, SSR markers and the molecular genetic map have provided essential resources and tools for modern genetic and genomic analyses of the chickpea genome. Using the SSR markers and genetic map, we mapped the genes and loci for flowering time and Ascochyta responses; one major QTL and a few minor QTLs have been identified for Ascochyta response and one major QTL has been identified for flowering time. The genetic correlations between flowering time, grain weight and Ascochyta response have been established. These results have provided essential tools and knowledge for effective manipulation and enhanced breeding of the traits in chickpea.
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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, August 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 performed with F1 hybrids of wheat and their parental cultivars. CMS in 95 RILs ranged from 76.5% to 22.4% with 71.5% and 31.3% in Danbata and Nacozari, respectively. The population segregated with a normal distribution across the full range of the parental values. Yield and biomass under non-stress conditions during the normal winter season at Bet Dagan dit not differ between the two parental cultivar, but the range of segregation for these traits in 138 RILs was very high and distinctly transgressive with a CV of 35.3% and 42.4% among lines for biomass and yield, respectively. Mean biomass and yield of the population was reduced about twofold when grown under the hot summer conditions (irrigated) at Bet Dagan. Segregation for biomass and yield was decreased relative to the normal winter conditions with CV of 20.2% and 23.3% among lines for biomass and yield, respectively. However, contrary to non-stress conditions, the parental cultivars differed about twofold in biomass and yield under heat stress and the population segregated with normal distribution across the full range of this difference. CMS was highly and positively correlated across 79 RILs with biomass (r=0.62**) and yield (r=0.58**) under heat stress. No such correlation was obtained under the normal winter conditions. All RILs expressed a set of HSPs under heat shock (37oC for 2 h). No variation was detected among RILs in high molecular weight HSP isoforms and they were similar to the patterns of the parental cultivars. There was a surprisingly low variability in low molecular weight HSP isoforms. Only one low molecular weight and Nacozari-specific HSP isoform (belonging to HSP 16.9 family) appeared to segregate among all RILs, but it was not quantitatively correlated with any parameter of plant production under heat stress or with CMS in this population. It is concluded that this Danbata/Nacozari F8 RIL population co-segregated well for thermotolerance and yield under heat stress and that CMS could predict the relative productivity of lines under chronic heat stress. Regretfully this population did not express meaningful variability for HSP accumulation under heat shock and therefore no role could be seen for HSP in the heat tolerance of this population. In the study of seven F1 hybrids and their parent cultivars it was found that heterosis (superiority of the F1 over the best parent) for CMs was generally lower than that for growth under heat stress. Hybrids varied in the rate of heterosis for growth at normal (15o/25o) and at high (25o/35o) temperatures. In certain hybrids heterosis for growth significantly increased at high temperature as compared with normal temperature, suggesting temperature-dependent heterosis. Generally, under normal temperature, only limited qualitative variation was detected in the patterns of protein synthesis in four wheat hybrids and their parents. However, a singular protein (C47/5.88) was specifically expressed only in the most heterotic hybrid at normal temperature but not in its parent cultivars. Parental cultivars were significantly different in the sets of synthesized HSP at 37o. No qualitative changes in the patterns of protein expression under heat stress were correlated with heterosis. However, a quantitative increase in certain low molecular weight HSP (mainly H14/5.5 and H14.5.6, belonging to the HSP16.9 family) was positively associated with greater heterosis for growth at high temperature. None of these proteins were correlated with CMS across hybrids. These results support the concept of temperature-dependent heterosis for growth and a possible role for HSP 16.9 family in this respect. Finally, when all experiments are viewed together, it is encouraging to find that genetic variation in wheat yield under chronic heat stress is associated with and well predicted by CMS as an assay of thermotolerance. On the other hand the results for HSP are elusive. While very low genetic variation was expressed for HSP in the RIL population, a unique low molecular weight HSP (of the HSP 16.9 family) could be associated with temperature dependant heterosis for growth.
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Paran, Ilan, and Molly Jahn. Analysis of Quantitative Traits in Pepper Using Molecular Markers. United States Department of Agriculture, January 2000. http://dx.doi.org/10.32747/2000.7570562.bard.
Texto completoResumen
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) Map fruit-specific ESTs and determine possible association with fruit QTL (6) Map the C locus that determines the presence and absence of capsaicinoids in pepper fruit and identify candidate genes for C. Background: Pungency, color, fruit shape and fruit size are among the most important fruit quality characteristics of pepper. Despite the importance of the pepper crop both in the USA and Israel, the genetic basis of these traits was only little known prior to the studies conducted in the present proposal. In addition, molecular tools for use in pepper improvement were lacking. Major conclusions and achievements: Our studies enabled the development of a saturated genetic map of pepper that includes numerous simple sequence repeat (SSR) markers and the integration of several independent maps into a single resource map that consists of over 2000 markers. Unlike previous maps that consisted mostly of tomato-originated RFLP markers, the SSR-based map consists of largely pepper markers. Therefore, the SSR and integrated maps provide ample of tools for use in marker-assisted selection for diverse targets throughout the Capsicum genome. We determined the genetic and molecular bases of qualitative and quantitative variation of pungency, the most unique characteristics of pepper fruit. We mapped and subsequently cloned the Pun1 gene that serves as a master key for capsaicinoids accumulation and showed that it is an acyltransferase. By sequencing the Pun1 gene in pungent and non-pungent cultivars we identified a deletion that abolishes the expression of the gene in the latter cultivars. We also identified QTLs that control capsaicinoids content and therefore pungency level. These genes will allow pepper breeders to manipulate the level of pungency for specific agricultural and industrial purposes. In addition to pungency we identified genes and QTLs that control other key developmental processes of fruit development such as color, texture and fruit shape. The A gene controlling anthocyanin accumulation in the immature fruit was found as the ortholog of the petunia transcription factor Anthocyanin2. The S gene required for the soft flesh and deciduous fruit nature typical of wild peppers was identified as the ortholog of tomato polygalacturonase. We identified two major QTLs controlling fruit shape, fs3.1 and fs10.1, that differentiate between elongated and blocky and round fruit shapes, respectively. Scientific and agricultural implications: Our studies allowed significant advancement of our understanding at the genetic and molecular levels of important processes of pepper fruit development. Concomitantly to gaining biological knowledge, we were able to develop molecular tools that can be implemented for pepper improvement.
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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, December 2013. http://dx.doi.org/10.32747/2013.7594399.bard.
Texto completoResumen
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 sequenced during the time of this project (cucumber was already sequenced when the project started watermelon and melon sequence became available during the project) but functional genomic tools are still missing. This research program had three major goals: 1. Develop whole genome cucumber and melon SNP arrays. 2. Develop and characterize cucumber populations segregating for fruit size. 3. Combine genomic tools, segregating populations, and phenotypic characterization to identify loci associated with fruit size. As suggested by the reviewers the work concentrated mostly in cucumber and not both in cucumber and melon. In order to develop a SNP (single nucleotide polymorphism) array for cucumber, available and newly generated sequence from two cucumber cultivars with extreme differences in shape and size, pickling GY14 and Chinese long 9930, were analyzed for variation (SNPs). A large set of high quality SNPs was discovered between the two parents of the RILs population (GY14 and 9930) and used to design a custom SNP array with 35000 SNPs using Agilent technology. The array was validated using 9930, Gy14 and F1 progeny of the two parents. Several mapping populations were developed for linkage mapping of quantitative trait loci (QTL) for fruit size These includes 145 F3 families and 150 recombinant inbred line (RILs F7 or F8 (Gy14 X 9930) and third population contained 450 F2 plants from a cross between Gy14 and a wild plant from India. The main population that was used in this study is the RILs population of Gy14 X 9930. Phenotypic and morphological analyses of 9930, Gy14, and their segregating F2 and RIL progeny indicated that several, likely independent, factors influence cucumber fruit size and shape, including factors that act both pre-anthesis and post-pollination. These include: amount, rate, duration, and plane of cell division pre- and post-anthesis and orientation of cell expansion. Analysis of F2 and RIL progeny indicated that factors influencing fruit length were largely determined pre-anthesis, while fruit diameter was more strongly influenced by environment and growth factors post-anthesis. These results suggest involvement of multiple genetically segregating factors expected to map independently onto the cucumber genome. Using the SNP array and the phenotypic data two major QTLs for fruit size of cucumber were mapped in very high accuracy (around 300 Kb) with large set of markers that should facilitate identification and cloning of major genes that contribute to fruit size in cucumber. In addition, a highly accurate haplotype map of all RILS was created to allow fine mapping of other traits segregating in this population. A detailed cucumber genetic map with 6000 markers was also established (currently the most detailed genetic map of cucumber). The integration of genetics physiology and genomic approaches in this project yielded new major infrastructure tools that can be used for understanding fruit size and many other traits of importance in cucumber. The SNP array and genetic population with an ultra-fine map can be used for future breeding efforts, high resolution mapping and cloning of traits of interest that segregate in this population. The genetic map that was developed can be used for other breeding efforts in other populations. The study of fruit development that was done during this project will be important in dissecting function of genes that that contribute to the fruit size QTLs. The SNP array can be used as tool for mapping different traits in cucumber. The development of the tools and knowledge will thus promote genetic improvement of cucumber and related cucurbits.
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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, May 1995. http://dx.doi.org/10.32747/1995.7570565.bard.
Texto completoResumen
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 promise to overcome some of these obstacles. The overall objective of this project was to determine whether QTLs for environmental stress tolerance could be effectively mapped in the perennial crop Citrus, using an extensive linkage map consisting of various types of molecular markers. Specific objectives were to: 1) Produce a highly saturated genetic linkage map of Citrus by continuing to place molecular markers of several types on the map. 2) Exploiting recently developed technology and already characterized parental types, determine whether QTLs governing cold acclimation can be mapped using very young seedling populations. 3) Determine whether the same strategy can be transferred to a different situation by mapping QTLs influencing Na+ and C1- exclusion (likely components of salinity tolerance) in the already characterized cross and in new alternative crosses. 4) Construct a YAC library of the citrus genome for future mapping and cloning.
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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.
Texto completoResumen
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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Orphan, Victoria, Gene Tyson, Christof Meile, Shawn McGlynn, Hang Yu, Grayson Chadwick, Jeffrey Marlow, 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), December 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.
Texto completoResumen
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 producción de papa en Colombia está afectada por el tizón tardío (P. infestans) y guatemalteco la polilla del tubérculo de la papa (T. solanivora) provoca pérdidas de hasta el 100% en el campo y el almacenamiento. Por lo tanto, en para comprender los factores genéticos que subyacen a la resistencia a P. infestans y T. solanivora, el objetivo principal de esta investigación es construir un mapa genético de alta saturación de SNP población tetraploide que se utilizará para mapear la resistencia QTL.
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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, February 2005. http://dx.doi.org/10.32747/2005.7586473.bard.
Texto completoResumen
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. The objectives of the proposal were: 1) to fine map three segregating ETL previously detected by a daughter design analysis of the Israeli dairy cattle population; 2) to determine the effects of ETL alleles in different families relative to the population mean; 3) for each ETL, to determine the number of alleles and allele frequencies. The ETL on Bostaurusautosome (BT A) 6 chiefly affecting protein concentration was localized to a 4 cM chromosomal segment centered on the microsatellite BM143 by the daughter design. The modified granddaughter design was applied to a single family. The frequency of the allele increasing protein percent was estimated at 0.63+0.06. The hypothesis of equal allelic frequencies was rejected at p<0.05. Segregation of this ETL in the Israeli population was confirmed. The genes IBSP, SPP1, and LAP3 located adjacent to BM143 in the whole genome cattle- human comparative map were used as anchors for the human genome sequence and bovine BAC clones. Fifteen genes within 2 cM upstream of BM143 were located in the orthologous syntenic groups on HSA4q22 and HSA4p15. Only a single gene, SLIT2, was located within 2 cM downstream of BM143 in the orthologous HSA4p15 region. The order of these genes, as derived from physical mapping of BAC end sequences, was identical to the order within the orthologous syntenic groups on HSA4: FAM13A1, HERC3. CEB1, FLJ20637, PP2C-like, ABCG2, PKD2. SPP, MEP, IBSP, LAP3, EG1. KIAA1276, HCAPG, MLR1, BM143, and SLIT2. Four hundred and twenty AI bulls with genetic evaluations were genotyped for 12 SNPs identified in 10 of these genes, and for BM143. Seven SNPs displayed highly significant linkage disequilibrium effects on protein percentage (P<0.000l) with the greatest effect for SPP1. None of SNP genotypes for two sires heterozygous for the ETL, and six sires homozygous for the ETL completely corresponded to the causative mutation. The expression of SPP 1 and ABCG2 in the mammary gland corresponded to the lactation curve, as determined by microarray and QPCR assays, but not in the liver. Anti-sense SPP1 transgenic mice displayed abnormal mammary gland differentiation and milk secretion. Thus SPP 1 is a prime candidate gene for this ETL. We confirmed that DGAT1 is the ETL segregating on BTA 14 that chiefly effects fat concentration, and that the polymorphism is due to a missense mutation in an exon. Four hundred Israeli Holstein bulls were genotyped for this polymorphism, and the change in allelic frequency over the last 20 years was monitored.