Relevant bibliographies by topics / Genetic and Phenotypic Correlations

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Genetic and Phenotypic Correlations'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Genetic and Phenotypic Correlations"

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Via, Sara, and Russell Lande. "Evolution of genetic variability in a spatially heterogeneous environment: effects of genotype–environment interaction." Genetical Research 49, no. 2 (April 1987): 147–56. http://dx.doi.org/10.1017/s001667230002694x.

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SummaryClassical population genetic models show that disruptive selection in a spatially variable environment can maintain genetic variation. We present quantitative genetic models for the effects of disruptive selection between environments on the genetic covariance structure of a polygenic trait. Our models suggest that disruptive selection usually does not alter the equilibrium genetic variance, although transient changes are predicted. We view a quantitative character as a set of character states, each expressed in one environment. The genetic correlation between character states expressed in different environments strongly affects the evolution of the genetic variability. (1) If the genetic correlation between character states is not ± 1, then the mean phenotype expressed in each environment will eventually attain the optimum value for that environment; this is the evolution of phenotypic plasticity (Via & Lande, 1985). At the joint phenotypic optimum, there is no disruptive selection between environments and thus no increase in the equilibrium genetic variability over that maintained by a balance between mutation and stabilizing selection within each environment. (2) If, however, the genetic correlation between character states is ± 1, the mean phenotype will not evolve to the joint phenotypic optimum and a persistent force of disruptive selection between environments will increase the equilibrium genetic variance. (3) Numerical analyses of the dynamic equations indicate that the mean phenotype can usually be perturbed several phenotypic standard deviations from the optimum without producing transient changes of more than a few per cent in the genetic variances or correlations. It may thus be reasonable to assume a roughly constant covariance structure during phenotypic evolution unless genetic correlations among character states are extremely high or populations are frequently perturbed. (4) Transient changes in the genetic correlations between character states resulting from disruptive selection act to constrain the evolution of the mean phenotype rather than to facilitate it.
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Feldman, Marcus W., Freddy B. Christiansen, and Sarah P. Otto. "Gene-culture co-evolution: teaching, learning, and correlations between relatives." Israel Journal of Ecology and Evolution 59, no. 2 (May 18, 2013): 72–91. http://dx.doi.org/10.1080/15659801.2013.853435.

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Heritability, the fraction of phenotypic variance attributable to the action of genes, is usually derived from a linear statistical partition of variance. In this paper we study a dichotomous phenotype whose transmission from parents to offspring depends on the parents’ phenotypes and the offspring’s genotype. Each individual is then represented as a phenogenotype. We derive expressions for each component of phenotypic variance and for covariances between relatives of various degrees. The resulting heritability estimates vary with the rates of phenotypic transmission as well as with the genetic contribution to the phenotype. Assortative mating by phenotype in parents is also shown to contribute to the correlations between relatives. In addition, we show that the frequency of alleles at genes affecting the phenotypes strongly affects standard heritability measures. This is important because for most complex traits these allele frequencies cannot be ascertained.
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Vaissiere, James, Jackson G. Thorp, Jue-Sheng Ong, Alfredo Ortega-Alonso, and Eske M. Derks. "Exploring Phenotypic and Genetic Overlap Between Cannabis Use and Schizotypy." Twin Research and Human Genetics 23, no. 4 (August 2020): 221–27. http://dx.doi.org/10.1017/thg.2020.68.

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AbstractThere is a well-established relationship between cannabis use and psychosis, although the exact nature of this relationship is not fully understood. Recent studies have observed significant genetic overlap between a diagnosis of schizophrenia and lifetime cannabis use. Expanding on this work, the current study aimed to examine whether genetic overlap also occurs for subclinical psychosis (schizotypy) and cannabis use, as well as examining the phenotypic association between the traits. Phenotypic correlations were calculated for a variety of schizotypy and cannabis phenotypes in the UK Biobank (UKB), and single nucleotide polymorphism (SNP)-based heritability estimates and genetic correlations were calculated for these UKB phenotypes as well as for several other variables taken from recent genomewide association studies. Positive phenotypic correlations were observed between 11 out of 12 pairs of the cannabis use and schizotypy phenotypes (correlation range .05–.18), indicating a robust association between increased symptoms of schizotypy and cannabis use. SNP-based heritability estimates for two schizotypy phenotypes remained significant after multiple testing correction: social anhedonia (h2SNP = .08, SE = .02, N = 4025) and ever seen an unreal vision (h2SNP = .35, SE = .10, N = 150,717). Finally, one significant genetic correlation was observed between schizotypy and cannabis use, a negative correlation between social anhedonia and number of times used cannabis (rg = −.30, p = .012). The current study suggests the relationship between cannabis use and psychosis is also seen in subclinical symptoms of psychosis, but further research with larger samples is needed to determine the biological mechanisms underlying this association.
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Cheverud, James M. "A Comparison of Genetic and Phenotypic Correlations." Evolution 42, no. 5 (September 1988): 958. http://dx.doi.org/10.2307/2408911.

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Cheverud, James M. "A COMPARISON OF GENETIC AND PHENOTYPIC CORRELATIONS." Evolution 42, no. 5 (September 1988): 958–68. http://dx.doi.org/10.1111/j.1558-5646.1988.tb02514.x.

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Winship, I. M., J. M. Connor, and P. H. Beighton. "Genetic heterogeneity in tuberous sclerosis: phenotypic correlations." Journal of Medical Genetics 27, no. 7 (July 1, 1990): 418–21. http://dx.doi.org/10.1136/jmg.27.7.418.

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Schwartz, Christopher J., and Timothy M. D'Alfonso. "Breast cancers with special genetic-phenotypic correlations." Diagnostic Histopathology 27, no. 4 (April 2021): 155–63. http://dx.doi.org/10.1016/j.mpdhp.2021.01.003.

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Minica, Camelia C., Dorret I. Boomsma, Sophie van der Sluis, and Conor V. Dolan. "Genetic Association in Multivariate Phenotypic Data: Power in Five Models." Twin Research and Human Genetics 13, no. 6 (December 1, 2010): 525–43. http://dx.doi.org/10.1375/twin.13.6.525.

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This article concerns the power of various data analytic strategies to detect the effect of a single genetic variant (GV) in multivariate data. We simulated exactly fitting monozygotic and dizygotic phenotypic data according to single and two common factor models, and simplex models. We calculated the power to detect the GV in twin 1 data in an ANOVA of phenotypic sum scores, in a MANOVA, and in exploratory factor analysis (EFA), in which the common factors are regressed on the genetic variant. We also report power in the full twin model, and power of the single phenotype ANOVA. The results indicate that (1) if the GV affects all phenotypes, the sum score ANOVA and the EFA are most powerful, while the MANOVA is less powerful. Increasing phenotypic correlations further decreases the power of the MANOVA; and (2) if the GV affects only a subset of the phenotypes, the EFA or the MANOVA are most powerful, while sum score ANOVA is less powerful. In this case, an increase in phenotypic correlations may enhance the power of MANOVA and EFA. If the effect of the GV is modeled directly on the phenotypes in the EFA, the power of the EFA is approximately equal to the power of the MANOVA.
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Cheverud, James M., and Larry J. Leamy. "Quantitative genetics and the evolution of ontogeny. III. Ontogenetic changes in correlation structure among live-body traits in randombred mice." Genetical Research 46, no. 3 (December 1985): 325–35. http://dx.doi.org/10.1017/s0016672300022813.

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SUMMARYOntogenetic series of phenotypic, additive genetic, maternal and environmental correlation matrices are presented and interpreted in the light of recent models for the Ontogenetic origin and variation in correlation between traits. A total of 432 mice from 108 full-sib families raised in a cross-fostering design were used to estimate the various components of phenotypic correlation for five live-body traits at eight ages. The level of genetic and phenotypic correlation decreased with age, while levels of maternal and environmental correlation remained more or less constant. Genetic correlations probably decreased due to compensatory growth. Phenotypic correlations decreased primarily due to the relative decrease in importance of highly correlated maternal effects and consequent increase in poorly correlated environmental effects as portions of phenotypic variation. The effect of compensatory growth on genetic correlation was also responsible for a portion of the decline in phenotypic correlation. Phenotypic correlation patterns remained constant over the ages studied here. It also seems likely the genetic, maternal and environmental correlation patterns do not change with age for the characters analysed.
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HADFIELD, J. D., A. NUTALL, D. OSORIO, and I. P. F. OWENS. "Testing the phenotypic gambit: phenotypic, genetic and environmental correlations of colour." Journal of Evolutionary Biology 20, no. 2 (March 2007): 549–57. http://dx.doi.org/10.1111/j.1420-9101.2006.01262.x.

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Dissertations / Theses on the topic "Genetic and Phenotypic Correlations"

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Habib, Farhat Abbas. "Genotype-phenotype correlation using phylogenetic trees." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1187297400.

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Gaya, Leila de Genova. "Estudo genético da qualidade de carne em linhagem macho de frangos de corte." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/74/74131/tde-05102006-094103/.

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O presente trabalho teve como objetivo estimar os parâmetros genéticos e fenotípicos das características de qualidade de carne e de características de desempenho, carcaça e composição corporal em uma linhagem macho de frangos fornecida pela Agroceres Ross Melhoramento Genético de Aves S. A. As aves faziam parte do programa denominado sib test, ou teste de irmãos, aonde são coletadas informações de carcaça dos irmãos dos indivíduos a serem selecionados na referida linhagem, estes chamados de rebanho elite. As características de desempenho analisadas foram peso à seleção (PS), peso ao abate (PA) e medidas de ultra-sonografia de músculo peitoral (US). As características de carcaça analisadas foram o peso de peito (PPEI), o peso eviscerado (PE) e o peso de pernas (PPER) e as características de composição corporal analisadas foram o peso da gordura abdominal (GOR), o peso do fígado (FIG) e o peso do coração (COR). As características de qualidade de carne analisadas foram: medida de pH inicial (pHi), medida de pH em 6 horas após o abate (pH6), medida de pH final (pHf), amplitude inicial de queda de pH (AMi), amplitude final de queda de pH (AMf), teor de luminosidade (L*), teor de vermelho (a*), teor de amarelo (b*), perdas de água por exsudação (EXSU), perdas de água por descongelamento (CONG), perdas de água por cozimento (COZ) e força de cisalhamento (FC). Os componentes de (co) variância foram estimados por verossimilhança restrita, utilizando-se o programa MTDFREML. A matriz de parentesco foi composta por 107.154 animais. Para as características pH6, pHf e L* foram estimados coeficientes de herdabilidade moderados; para as demais características estes coeficientes foram baixos. As estimativas de correlações genéticas obtidas não foram indicativas de associações importantes entre as características de qualidade de carne e as características de desempenho, carcaça e composição corporal, exceto pela seleção a favor de PS, que pode reduzir as perdas de água da carne. As estimativas de correlações genéticas encontradas entre as características de qualidade de carne puderam contribuir para o entendimento dos mecanismos relacionados à qualidade da carne na linhagem analisada, de modo que CONG, FC e L* foram características capazes de trazer respostas correlacionadas favoráveis às demais e em maior ou menor grau apresentarem capacidade de resposta à seleção, recomendando-se sua utilização como critério de seleção quando na existência de necessidade de melhoria na qualidade da carne na linhagem estudada. Contudo, esta necessidade não foi aparente, uma vez que as tendências genéticas das características de qualidade de carne, além de terem sido de pequena magnitude, foram em sua maioria favoráveis à qualidade da carne da linhagem analisada.
This research was conducted to estimate genetic and phenotypic parameters of meat quality, performance, carcass and body composition traits in a male broiler line provided by Agroceres Ross Melhoramento Genético de Aves S. A. Broilers measured belonged to a sib test program, in which data from sibs of the individuals to be selected in this line, called elite flock, are collected. Performance traits analyzed were body weight at selection (PS), body weight at slaughter (PA) and ultrasound records of pectoral muscle (US). Carcass traits analyzed were meat breast weight (PPEI), eviscerated body weight (PE) and leg weight (PPER) and the body composition traits analyzed were abdominal fat weight (GOR), liver weight (FIG) and heart weight (COR). Meat quality traits analyzed were: initial pH measure (pHi), pH measure at 6 hours after slaughter (pH6), final pH measure (pHf), initial range of pH fall (AMi), final range of pH fall (AMf), lightness (L*), redness (a*), yellowness (b*), weep losses (EXSU), drip losses (CONG), shrink losses (COZ) and shear force (FC). (Co) variance components were estimated by restricted maximum likelihood method, using the software MTDFREML. The numerator relationship matrix was composed by 107.154 individuals. For pH6, pHf and L*, moderate heritability coefficients were estimated; for the other traits these coefficients were low. Genetic correlation estimates obtained indicated a small association among meat quality traits and performance, carcass and body composition traits, except for the selection to PS, which seemed to be able to reduce water losses of meat. Genetic correlations estimates among meat quality traits could orientated the understanding of the mechanisms related to meat quality in the analyzed line; CONG, FC and L* seemed to be able to bring favorable correlationed responses, so it was recommended its use as selection criterion if existing the necessity of improving the meat quality in the analyzed line. However, this necessity was not apparent, since the genetic trends of meat quality traits were small and favorable to meat quality in the analyzed broiler line.
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Rich, Kelly A. "Investigating Genotype-Phenotype Correlations in TTN-related Neuromuscular and/or Cardiomyopathy Conditions." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555059134283087.

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Booth, Kevin T. "Unraveling the genotypic and phenotypic complexities of genetic hearing loss." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6549.

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Hereditary hearing loss is the most common sensory disorder, affecting 1 in 500 newborns. There are more than 538 million individuals with genetic hearing loss worldwide and this number is expected to grow to 1 billion over the next three decades. Currently, the only option for individuals with hearing loss is mechanical intervention such as hearing aids or cochlear implants. In the past decade, many studies have highlighted the need for personalized gene therapy or molecular intervention to treat genetic deafness. However, in order to fulfill this vision a comprehensive understanding of the intricate mutation-gene-phenotype nuances and relationships is required. Toward this goal, we unraveled novel mutation-gene-phenotype associations and mechanisms in four deafness-causing genes (CIB2, COL11A1, CEACAM16 and DFNA5), by using a combination of in-depth phenotyping, human genetics, cutting edge genomic technologies, murine mutant models, and functional assays. These novel insights revealed mutations in CIB2 do not cause Usher Syndrome, mutations in COL11A1 can cause either non-syndromic or syndromic hearing loss, CEACAM16-related deafness is due to two distinct mechanisms, loss of function and gain of function, and coding variants can influence mRNA assembly and cause DFNA5-related hearing loss. Elucidating these novel mutation-gene-phenotype relationships has improved our knowledge of the pathogenic mechanisms underlying hearing loss and provided much needed answers to individuals seeking a diagnosis for their deafness. Recognizing the complexities associated with genetic hearing loss and the challenges in interpreting the clinical significance of genetic variants, we established the first deafness-specific variant database, the Deafness Variation Database (DVD), which classifies over 876,000 variants across 152 deafness-associated genes. This breadth of data provided us with a unique opportunity to explore the molecular landscape of deafness. We show that over 96% of coding variants are rare and novel and that mutational signatures are unique to each gene and are driven by minor allele frequency thresholds, variant effect, and protein domain. The mutational landscape we define shows complex gene-specific variability, making an understanding of these nuances foundational for improved accuracy in variant interpretation. Overall the work presented in this thesis improves our understanding of deafness biology, identifies novel targets for therapeutics and enhances clinical decision-making.
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Yildirim, Kubilay. "Inheritance Of Wood Specific Gravity And Its Genetic Correlation With Growth Traits In Young Pinus Brutia Progenies." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/2/12609264/index.pdf.

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In long term, to discover the genes responsible for wood production, genetic control of wood specific gravity (WSG) in Pinus brutia Ten. (Turkish red pine) open pollinated Ceyhan progeny trial, which was established with the seeds collected from 168 clones originated from six clonal Turkish red pine seed orchards was studied. Wood samples were taken by destructive sampling during the rouging of this trial at the age of seven. Specifically
(1) to examine the magnitude of family differences and its components for wood specific gravity (WSG) and growth traits (height, diameter and stem volume)
(2) to determine WSG inheritance and its genetic correlation with growth traits
and (3) to estimate breeding values of 168 families for the WSG and to predict genetic gain if selection is based on phenotypic, rouged and genotypic seed orchard by reselecting the best parents with respect to WSG. Differences among the 168 families for mean WSG was large (ranged from 0.35 to 0.44), as indicated by high individual (0.42+0.07) and family mean (0.55+0.03) heritabilities. Family differences and high heritabilities were also observed for all growth traits. Genetic correlations between WSG and growth traits were statistically insignificant (near zero), while low and insignificant negative phenotypic correlations among the same traits were observed. Realized genetic gain for single trait selection at age seven was insignificant (0.37 %) for WSG and 8.4 % for stem volume in phenotypic seed orchards. Average genetic gain in breeding zone after roguing, by leaving the best 20 clones in each seed orchard, reached 1.7 % for WSG and 16.1 % for stem volume. Genetic gain (relative to controls) at the age of seven obtained from the first generation genotypic seed orchards consisting the best 30 clones was estimated 5.2 % for WSG and 35 % for stem volume. Multi-trait selection was also proposed in this study for the same traits. Selection of best 10 families for the highest WSG and stem volume breeding values produce 5.6 % genetic gain for WSG and 27.7 % genetic gain for stem volume. For the future, the 168 families with known phenotypic and genotypic values regarding to WSG will be screened for the genes responsible for wood production.
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Webber, Troy Alan. "Genetic Moderation of Phenotypic and Neural Indicators of Peer Influenced Risk-taking Behavior: An Experimental Investigation." Scholar Commons, 2015. http://scholarcommons.usf.edu/etd/5825.

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Risk-taking behavior (RTB) is defined as behavior involving the probability of reward with concurrent probability of some negative outcome. Peer influence is among the most robust predictors of RTB, such that greater peer influence, particularly deviant or delinquent peer influence, is associated with increased RTB. Evidence suggests that those with genetic predispositions for RTB may also be more susceptible to peer influence as a function of genotype. Given that genetic polymorphisms within the dopaminergic system have evidenced associations with various forms of RTB and delinquent peer affiliation, it is possible that these genes may interact with peer influence to predict increased RTB, a process called gene × environment interaction (G×E). We expected that those genetically at risk would take more risks in the presence of a peer than alone. To test this effect, five polymorphisms within the dopaminergic system were genotyped in a sample of 85 undergraduate students. Participants completed a behavioral risk task alone and in the presence of a peer providing "risky" feedback. No significant G×Es were identified for any of the dependent variables. However, participants took significantly more risks in the presence of a risky peer than when taking risks alone. These results suggest that G×E may not be a relevant process for peer-influenced RTB during late adolescence. It is possible that G×E is a relevant process during early adolescence, while gene-environment correlation (rGE) is the dominant process during late adolescence. Future research would benefit from testing whether these genes are relevant to G×E in early adolescence, as well as to rGE during late adolescence.
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Kerzienė, Sigita. "Kiaulių reprodukcinių savybių genetinė analizė ir ryšys su produktyvumo požymiais." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20051123_090911-57122.

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Objective of the research - to evaluate, using up-to-date statistical–genetic methods, the reproductive characteristics of pig breeds bred in Lithuania, to determine correlation of the characteristics with productivity traits, and to develop an optimised system of pigs genetic evaluation by BLUP method. Tasks of the research was: to determine influence of genetic and non-genetic factors in pigs reproductive characteristics, to evaluate the additive-genetic heritability parameters, and co-response of reproduction traits; to evaluate influence of reproductive characteristics on productivity traits, phenotype and genetic co-response; to develop an optimised pigs genetic evaluation system employing BLUP method, estimating pigs reproductive and productive characteristics, using the integrated multivariate model; to evaluate tendencies of pigs genetic improvement. Novelty of the research: using the method of unifactor and multifactor dispersion analysis, leverage of genetic and non-genetic factors on reproductive characteristics of pigs, breed in Lithuania, was determined; heritability parameters of reproductive characteristics were determined, using modern software; genetic and phenotype co-response of the reproductive characteristics was estimated; genetic correlation between reproductive characteristics and productivity traits was evaluated, using statistical-genetic methods, for the first time in Lithuania; optimised multivariate model for determination of reproductive and... [to full text]
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Vicente, António Pedro Andrade. "Characterization and selection of the Lusitano horse breed." Doctoral thesis, Universidade de Lisboa. Faculdade de Medicina Veterinária, 2015. http://hdl.handle.net/10400.5/8646.

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Tese de Doutoramento em Ciências Veterinárias. Especialidade de Produção Animal
Um estudo aprofundado de caracterização genética e estratégias de seleção na raça equina Lusitana foi realizado para identificar os principais fatores que afetam a variabilidade genética desta população e fornecer informações para o delineamento de um programa de melhoramento genético sustentável. Foi analisada a informação genealógica registada entre 1824-2009, incluindo 53417 animais. O intervalo de gerações médio foi de 11.33±5.23 e 9.71±4.48 anos para garanhões e éguas, respetivamente. Os animais nascidos entre 2005 e 2009 tiveram um número médio de gerações conhecidas de 11.20±0.71 e consanguinidade média de 11.34±7.48%. O aumento anual da consanguinidade foi de 0.173±0.070, a que corresponde um tamanho efetivo da população de 28. O número efetivo de fundadores, ascendentes e coudelarias fundadoras foi de 27.5, 11.7 e 5.4, respetivamente. Estes resultados refletem uma forte ênfase em algumas linhas e indicam a necessidade de uma gestão cuidadosa da diversidade genética para o futuro. Foram utilizados modelos mistos para estimar parâmetros genéticos, efeitos fixos e predizer valores genéticos para características morfo-funcionais por análises uni e multivariadas. Os caracteres morfológicos incluídos foram as pontuações parciais atribuídas a mais de 18 mil animais na sua inscrição como reprodutores (classificação de cabeça/pescoço, espádua/garrote, peitoral/costado, dorso/rim, garupa, membros e conjunto de formas), para além da pontuação final (FS), altura ao garrote (HW) e andamentos (GA). Funcionalmente foram considerados os resultados das provas de ensino (WEDT) e maneabilidade (WEMT) em Equitação de Trabalho (WE, cerca de 1500 resultados em 200 cavalos), e Dressage (CD, cerca de 12000 resultados em 760 cavalos). Os efeitos fixos para a morfologia foram a coudelaria, ano, sexo, consanguinidade e idade. Para a funcionalidade foram a prova, nível de competição, sexo, consanguinidade e idade. A heritabilidade estimada (h2) para as pontuações morfológicas parciais variou entre 0.12 e 0.18, à exceção dos membros (0.07). Foi também de 0.18 para FS, 0.61 para HW e 0.17 para GA. Para a performance a h2 foi de 0.32 (WEDT e CD) e 0.18 (WEMT). As correlações genéticas entre os vários componentes parciais de morfologia foram positivas mas muito variáveis (0.08-0.77). As relações genéticas entre morfologia e funcionalidade foram favoráveis, indicando que a morfologia/andamentos podem ser usados como caracteres complementares na seleção para a WE ou CD. A depressão consanguínea foi de magnitude muito reduzida para todos os caracteres analisados. Os valores genéticos estimados para a morfologia e funcionalidade apresentam grande variabilidade, mostrando que a seleção pode ser eficaz, mas a tendência genética observada ao longo dos últimos anos foi moderadamente positiva. Compararam-se ainda duas fontes diferentes de informação (pedigrees vs microssatélites) enquanto indicadores da diversidade genética e estrutura populacional do cavalo Lusitano. Para além das genealogias completas, foram utilizados dados sobre 6 ou 8 microssatélites genotipados em cerca de 19 mil Lusitanos entre 1998-2007. A consanguinidade obtida via genealogias revelou-se melhor estimador da consanguinidade molecular do que o inverso, mas apresentou uma correlação modesta com a heterozigotia multilocus (6% da variabilidade explicada). As taxas de consanguinidade por geração estimadas pelos dois métodos foram semelhantes. As distâncias genéticas entre as principais coudelarias foram comparáveis (correlação entre distâncias genéticas FST de 0.82). Globalmente, os parâmetros calculados a partir de informação genealógica são melhores preditores dos indicadores moleculares. No entanto, ao nível da população, os parâmetros de diversidade genética estimados, tendências ao longo do tempo e subestrutura da população são muito semelhantes quando estimados pelo pedigree ou por marcadores microssatélites.
ABSTRACT - Characterization and selection of the Lusitano horse breed - An in-depth study of characterization and evaluation of selection strategies in the Lusitano horse breed was conducted to identify factors affecting the genetic variability of the breed and provide baseline information for the establishment of a sustainable genetic improvement program. Pedigree records collected in 53417 animals born from 1824 to 2009 were used. The mean generation interval was 11.33±5.23 and 9.71±4.48 years for sires and dams, respectively. For animals born between 2005 and 2009, the mean number of equivalent generations was 11.20±0.71 and the average inbreeding was 11.34±7.48%. The rate of inbreeding per year was 0.173±0.070, and the corresponding effective population size was about 28. The effective number of founders, ancestors and studs was 27.5, 11.7 and 5.4, respectively. These results reflect a strong emphasis placed on a few sire-families and raise concerns regarding the conservation of genetic diversity for the future. Mixed model procedures were used to estimate genetic parameters, fixed effects and genetic trends for morpho-functional traits in Lusitano horses by uni- and multivariate animal models. Morphological traits included were partial scores attributed to more than 18000 horses at the time of registration in the studbook and included the classification of head/neck, shoulder/withers, chest/thorax, back/loin, croup, legs and overall impression, plus a final score (FS) and a score for gaits (GA) and the measurement of height at withers (HW). For functionality, the traits considered were scores obtained in dressage (WEDT) and maneability (WEMT) trials of working equitation (WE, about 1500 records by 200 horses), and classical dressage (CD, about 12130 records by nearly 760 horses). Fixed effects considered in the analyses of morphology, GA and FS were stud, year, sex, inbreeding and age. For functionally traits, the fixed effects were event, level of competition, sex, inbreeding and age. Heritability (h2) estimates for all partial morphological scores ranged between 0.12 and 0.18, except for legs (0.07), and were 0.18 for FS, 0.61 for HW and 0.17 for GA. For performance, h2 was 0.32 for WEDT and CD and 0.18 for WEMT. The genetic correlations among partial components of morphology were positive but widely different (0.08 to 0.77). The favourable genetic relationships existing between morphology and performance indicate that morphology and gaits traits can be used to enhance selection response when the improvement of WE or CD is intended. The magnitude of inbreeding depression was small for all the traits analyzed. The estimated breeding values for morphology, gaits and WE presented a large variability, indicating that selection can be effective, but the genetic trend observed over the last few years was positive but moderate for all traits. The assessment of genetic diversity and population structure obtained by either pedigree data or microsatellite markers was compared. The same pedigree database was used and, in addition, data on either 6 or 8 microsatellite markers genotyped in more than 19000 horses, from 1998-2007. Genealogical inbreeding was a better predictor of molecular inbreeding than the opposite, but it had a modest correlation with multilocus heterozygosity (6% of its variability). Still, the rates of inbreeding per generation estimated by the two methods were very similar. Genetic distances among the major studs producing Lusitano horses were comparable when they were estimated from pedigree or molecular information, with a correlation between FST distances of 0.82, and similar dendrograms were obtained in both cases. Overall, estimates derived from a reduced number of microsatellites or from pedigrees are poorly correlated when considered at the individual level, but parameters derived from pedigree are better predictors of molecular-derived indicators. However, when considered at the breed-level, the estimated diversity parameters, time trends and population substructure are very similar when genealogical data or microsatellite markers are considered.
Instituto Politécnico de Santarém
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Elsayed, Walid Shaaban Moustafa. "Dissecting the pathway of human tooth development through a genetic survey of human Amelogenesis imperfecta : phenotype/genotype correlations and relevance to biomineralisation." Thesis, University of Leeds, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.555902.

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Amelogenesis imperfecta (AI) is the name given to a clinically and genetically heterogeneous group of enamel biomineralisation defects with Mendelian patterns of inheritance. Enamel quantity and/or quality are affected, with inappropriate retention of enamel matrix proteins in the most cases, resulting in hypoplastic and/or hypomineralised phenotypes. AI most commonly occurs in apparent isolation from other co-segregating clinical abnormalities ('non-syndromic AI'). Instances of AI forming part of a diverse range of syndromes are recognised, but poorly described ('syndromic AI'). To date, reported studies have focused on the X-linked and dominant forms of non-syndromic AI which relate to two enamel matrix proteins (AMELX and ENAM) and more recently a cellular protein of unknown function (FAM83H). Only four mutations in 3 genes (ENAM, KLK4 and MMP20) have been described for autosomal recessive non-syndromic AI. This study aims to gain new insight into the genetic basis and phenotype of autosomal recessively inherited hypomineralised AI, both syndromic and non- syndromic forms, through genetic analysis in consanguineous families. A whole-genome SNP autozygosity screen in a non-syndrmoic AI family of Pakistani origin identified a new locus on chromosome 15q21.3. Sequencing .candidate genes in multiple families revealed four different mutations in the poorly characterised WOR72 gene which resulted in autosomal recessive non-syndromic AI (chapter Ill). Deciduous teeth - VI - extracted as part of clinical care from one individual with homozygous WOR72 mutations, revealed normal enamel rod architecture, yet with abnormal inter-rod enamel revealed by scanning electron microscopy (SEM). Energy-dispersive X- ray (EOX) spectra were characterised by normal carbon (C) and nitrogen (N) peaks, excluding the possibility of retention of enamel matrix protein. However, transverse microradiography (TMR) revealed mineral content values significantly lower when compared to normal teeth, indicating hypomineralisation (chapter Ill). A whole-genome SNP autozygosity screen in a family, with syndromic AI and hypohidrosis identified a second locus on chromosome 11 p15.5- q13.1. Sequencing the exons of every gene within the linked region revealed a missense mutation in the STlM1 gene, which is a calcium ion sensor protein (chapter IV). Analyses of extracted permanent and exfoliated deciduous teeth from the proband patient (VII:3) in family P21 confirmed reduced mineral (as determined by TMR) and increased organic content in enamel (determined by EOX). SEM revealed poor quality enamel prisms which were obscured by an amorphous material. This amorphous material was removed by incubation with a-chymotrypsin, but not by incubation with lipase, which was consistent with the inappropriate presence of protein in the enamel. Western blot analyses of protein extracted from the affected enamel indicated the presence of albumin. The dentine was characterised by abnormal morphology on SEM. The only other clinical abnormality identified was hypohidrosis. In particular, there was no apparent involvement of other ectodermal tissues. 1 } ].
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Beyene, Yoseph Aydagn. "Genetic analysis of traditional Ethiopian Highland Maize (Zea Mays L.) using molecular markers and morphological traits : implication for breeding and conservation." Thesis, University of Pretoria, 2005. http://hdl.handle.net/2263/30529.

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Knowledge of the genetic variation of crop collections is essential for their efficient use in plant breeding programs. The Ethiopian Highland Maize Germplasm Collection Mission was launched throughout the highlands of Ethiopia in 1998 and 287 traditional maize accessions were collected from farmers’ fields. To date, no information was available on the morphological and genetic diversity in this important collection. Various molecular marker techniques and quantitative genetics approaches were applied to accurately unravel the extent of phenotypic and genetic diversity, to study patterns of morphological and molecular variation and to determine association of molecular markers with quantitative trait variation, with the view of designing a sound breeding program and management strategy for maize in the highlands of Ethiopia. The morphological study confirmed that traditional Ethiopian highland maize accessions contain large amounts of variation for agro-morphological traits. The broad trait diversity observed among the accessions suggested ample opportunities for the genetic improvement of the crop through selection directly from the accessions and/ or the development of inbred lines for a future hybrid program. Selection practices followed by local farmers are mostly consistent within agroecology and gave rise to morphologically distinct maize accessions in different agroecologies. This underscores the importance of considering farmers’ knowledge of diversity in the collection and evaluation of local accessions. The results of amplified fragment length polymorphism (AFLP) and microsatellite or simple sequence repeat (SSR) marker analyses showed that bulking leaf samples from 15 individual plants per out-bred accession is an effective means of producing representative profiles of individual plants, thereby reducing the cost of DNA extraction and subsequent marker analysis of open-pollinated varieties. Cluster analyses based on AFLP and SSR data showed that most of the accessions collected from the Northern agroecology were genetically distinct from the Western and Southern accessions suggesting that differentiation for adaptive traits for drought conditions may have occurred in the Northern accessions. However, there was very little genetic differentiation between the Western and Southern accessions suggesting gene flow between the two agroecologies and recent introduction of similar improved varieties in these agroecoogies . In both marker systems, high mean genetic diversity was observed among the traditional Ethiopian highland maize accessions. This is possibly due to (i) the continuous introduction of maize from abroad by different organizations; (ii) genetic variation generated through farmers management practices; and (iii) the presence of different environmental conditions in the highlands of Ethiopia to which local landraces may have been adapted. The correlation between the morphological dissimilarity matrix and the matrices of genetic dissimilarity based on SSR and AFLP markers were 0.43 and 0.39, respectively (p = 0.001 in both cases). The correlation between SSR and AFLP dissimilarity matrices was 0.67 (p = 0.001). These significant correlations indicate that the three independent sets of data likely reflect the same pattern of genetic diversity, and validate the use of the data to calculate the different diversity statistics for Ethiopian highland maize accessions. From this study, three groups of maize accessions with distinctive genetic profiles and morphological traits were identified that will be useful for future collection, conservation and breeding programs of maize for the highlands of Ethiopia. A pilot association study using SSR markers and quantitative trait variation indicated that molecular markers could be useful to identify genetic factors controlling earliness, tallness, grain yield and associated traits, which could be exploited by various breeding schemes. The analytical tools outlined in this dissertation can be a useful tool in managing genetic variation of open-pollinated crops and will aid in the conservation of unique genetic diversity. Production stability and global food security are linked to the conservation and exploitation of worldwide genetic resources and this research attempts to add to that body of knowledge. Copyright 2005, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. Please cite as follows: Beyene, YA 2005, Genetic analysis of traditional Ethiopian Highland Maize (Zea Mays l.) using molecular markers and morphological traits : implication for breeding and conservation, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd < http://upetd.up.ac.za/thesis/available/etd-02212006-112610 / >
Thesis (PhD (Genetics))--University of Pretoria, 2005.
Genetics
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Books on the topic "Genetic and Phenotypic Correlations"

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Phenotypic variation: Exploration and functional genomics. Oxford: Oxford University Press, 2010.

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Lee, Mark Joon-Sung. Phenotypic and genetic characterization of borderline oxacillin-resistant Staphylococcus aureus. Ottawa: National Library of Canada, 1999.

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Symposium on Phenotypic Variation in Populations: Relevance to Risk Assessment (1986 Brookhaven National Laboratory). Phenotypic variation in populations: Relevance to risk assessment. New York: Plenum Press, 1988.

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Podmore, S. M. Phenotypic and molecular genetic studies on the production of the calcium-dependent antibiotic of streptomyces coelicolor A3(2). Manchester: UMIST, 1995.

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David, Epel, ed. Ecological developmental biology: Integrating epigenetics, medicine, and evolution. Sunderland, Mass., U.S.A: Sinauer, 2009.

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Cazeneuve, Cécile, and Alexandra Durr. Genetic and Molecular Studies. Oxford University Press, 2014. http://dx.doi.org/10.1093/med/9780199929146.003.0006.

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Huntington’s disease (HD) is a rare inherited neurologic disorder due to a single mutational mechanism in a large gene (HTT). The mutation is an abnormal CAG repeat expansion, which is translated to a polyglutamine stretch in the huntingtin protein. The growing field of repeat expansion disorders benefits greatly from the lessons learned from the role of the CAG repeat expansion in HD and its resulting phenotype–genotype correlations. The molecular diagnosis can be difficult, and there are some pitfalls for accurate sizing of the CAG repeat, especially in juvenile HD and for intermediate alleles. Correlation between CAG length and age of onset accounts for up to 72% of the variance in different populations, but the search for genes modifying age of onset or progression of HD is still ongoing.
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Aaronson, Stuart A. Genetic and Phenotypic Markers of Tumors. Springer, 2012.

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Aaronson, Stuart A., and Luigi Frati. Genetic and Phenotypic Markers of Tumors. Plenum Publishing Corporation, 1985.

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Laboratory), Symposium on Phenotypic Variation in Populations: Relevance to Risk Assessment (1986 Brookhaven National. Phenotypic variation in populations. Plenum, 1988.

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Carlson, Aldrich John, ed. Phenotypic responses and individuality in aquatic ectotherms. Ashford, County Wicklow: JAPAGA, 1989.

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Book chapters on the topic "Genetic and Phenotypic Correlations"

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Sklenar, P., L. KovaČev, N. ČAČiĆ, S. Mezei, and N. Nagl. "Genetic and Phenotypic Correlations for Some Sugar Beet Root Characteristics." In Progress in Botanical Research, 569–72. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-011-5274-7_131.

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Simpson, J. L. "Phenotypic-Karyotypic Correlations of Gonadal Determinants: Current Status and Relationship to Molecular Studies." In Human Genetics, 224–32. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-71635-5_27.

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Brun, Francesca, Concetta Di Nora, Michele Moretti, Anita Spezzacatene, Luisa Mestroni, and Fulvio Camerini. "Genetics: Genotype/Phenotype Correlations in Cardiomyopathies." In Clinical Echocardiography and Other Imaging Techniques in Cardiomyopathies, 13–24. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-06019-4_2.

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Mornet, Etienne. "Molecular Genetics of Hypophosphatasia and Phenotype-Genotype Correlations." In Subcellular Biochemistry, 25–43. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-7197-9_2.

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Kaneko, Kunihiko. "Genetic Evolution with Phenotypic Fluctuations." In Understanding Complex Systems, 255–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/978-3-540-32667-0_10.

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Motulsky, A. G. "Human Genetic Individuality and Risk Assessment." In Phenotypic Variation in Populations, 7–9. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-5460-4_2.

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Arnheim, Norman. "New Technologies for Studying Human Genetic Variation." In Phenotypic Variation in Populations, 37–44. Boston, MA: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-5460-4_5.

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Gal, Andreas. "Molecular Genetics of Fabry Disease and Genotype–Phenotype Correlation." In Fabry Disease, 3–19. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9033-1_1.

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Jackson, David. "Promoting Phenotypic Diversity in Genetic Programming." In Parallel Problem Solving from Nature, PPSN XI, 472–81. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15871-1_48.

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Moore, Paul H. "Phenotypic and Genetic Diversity of Papaya." In Genetics and Genomics of Papaya, 35–45. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8087-7_3.

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Conference papers on the topic "Genetic and Phenotypic Correlations"

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Bhuva, Meha, Richard Sandford, and William Griffiths. "O01 Genetic analysis and phenotypic correlation in ductal plate malformation." In Abstracts of the British Association for the Study of the Liver Annual Meeting, 22–24 November 2021. BMJ Publishing Group Ltd and British Society of Gastroenterology, 2021. http://dx.doi.org/10.1136/gutjnl-2021-basl.1.

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Geyer, FC, KA Burke, AD Papanastatiou, GS Macedo, E. Brogi, L. Norton, YH Wen, B. Weigelt, and JS Reis-Filho. "Abstract P1-05-04: Intra-tumor genetic heterogeneity and histologic heterogeneity within metaplastic breast cancers: Genotypic-phenotypic correlations." In Abstracts: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.sabcs16-p1-05-04.

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Cserepes, Mihaly T., Zita Hegedus, Ivan Ranđelović, Istvan Kenessey, Mónika Meilinger-Dobra, Kristóf G. Csikó, Andrea Ladanyi, Éva Remenár, and Jozsef Tovari. "Abstract 1863: Correlations of genetic variation R521K of EGF receptor and thein vitro, in vivoand clinical phenotypes of head and neck cancers after cetuximab treatment." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-1863.

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Smith, Davy, Laurissa Tokarchuk, and Geraint Wiggins. "Harnessing Phenotypic Diversity towards Multiple Independent Objectives." In GECCO '16: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908961.2931654.

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Hagg, Alexander, Martin Zaefferer, Jörg Stork, and Adam Gaier. "Prediction of neural network performance by phenotypic modeling." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3319619.3326815.

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Delattre, Olivier. "Abstract IA15: Genetic and phenotypic diversity in Ewing sarcoma." In Abstracts: AACR Special Conference: Advances in Pediatric Cancer Research: From Mechanisms and Models to Treatment and Survivorship; November 9-12, 2015; Fort Lauderdale, Florida. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.pedca15-ia15.

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"The phenotypic manifestation of Wolbachia genetic diversity in host fitness." In Bioinformatics of Genome Regulation and Structure/ Systems Biology. institute of cytology and genetics siberian branch of the russian academy of science, Novosibirsk State University, 2020. http://dx.doi.org/10.18699/bgrs/sb-2020-132.

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Veenstra, Frank, Emma Hart, Edgar Buchanan, Wei Li, Matteo De Carlo, and Agoston E. Eiben. "Comparing encodings for performance and phenotypic exploration in evolving modular robots." In GECCO '19: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3319619.3322054.

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Huizinga, Joost, Jean-Baptiste Mouret, and Jeff Clune. "Does Aligning Phenotypic and Genotypic Modularity Improve the Evolution of Neural Networks?" In GECCO '16: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2908812.2908836.

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Belash, Vasiliy, Zhanna Mironova, Vasiliy Trofimov, Mikhail Zaraiski, Alexei Sazanov, and Anna Ulitina. "Phenotypic and molecular-genetic features of asthma-COPD overlap syndrome (ACOS)." In Annual Congress 2015. European Respiratory Society, 2015. http://dx.doi.org/10.1183/13993003.congress-2015.pa647.

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Reports on the topic "Genetic and Phenotypic Correlations"

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

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Karlan, Beth Y. Genetic Definition and Phenotypic Determinants of Human Ovarian Carcinomas. Fort Belvoir, VA: Defense Technical Information Center, October 2000. http://dx.doi.org/10.21236/ada394004.

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Karlan, Beth Y. Genetic Definition and Phenotypic Determinants of Human Ovarian Carcinomas. Fort Belvoir, VA: Defense Technical Information Center, October 2002. http://dx.doi.org/10.21236/ada412766.

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Karlan, Beth Y. Genetic Definition and Phenotypic Determinants of Human Ovarian Carcinomas. Fort Belvoir, VA: Defense Technical Information Center, October 2003. http://dx.doi.org/10.21236/ada422218.

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Lue, Michael. Phenotypic and Mutational Consequences of Mitochondrial ETC Genetic Damage. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2199.

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Dimitrov, Roumen, and Dilnora Gouliamova. Genetic and Phenotypic Cut-off Values for Species and Genera Discrimination of the Kazachstania Clade. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, March 2019. http://dx.doi.org/10.7546/crabs.2019.03.09.

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

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

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Stock, Joseph D., Julia A. Calderón Díaz, Max F. Rothschild, Benny E. Mote, and Kenneth J. Stalder. Phenotypic and Genetic Associations of Objectively Evaluated Replacement Female Feet and Leg Joint Conformation at Selection and Post First Parity. Ames (Iowa): Iowa State University, January 2018. http://dx.doi.org/10.31274/ans_air-180814-396.

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Sacks, Erik. Final Report: Quantifying phenotypic and genetic diversity of Miscanthus sacchariflorus to facilitate knowledge-directed improvement of M. ×giganteus (M. sinensis × M. sacchariflorus) and sugarcane. Office of Scientific and Technical Information (OSTI), October 2019. http://dx.doi.org/10.2172/1570949.

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