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Journal articles on the topic 'Polygenic traits'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

BARTON, N. H. "Clines in polygenic traits." Genetical Research 74, no. 3 (1999): 223–36. http://dx.doi.org/10.1017/s001667239900422x.

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This article outlines theoretical models of clines in additive polygenic traits, which are maintained by stabilizing selection towards a spatially varying optimum. Clines in the trait mean can be accurately predicted, given knowledge of the genetic variance. However, predicting the variance is difficult, because it depends on genetic details. Changes in genetic variance arise from changes in allele frequency, and in linkage disequilibria. Allele frequency changes dominate when selection is weak relative to recombination, and when there are a moderate number of loci. With a continuum of alleles

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2

ZENG, WEN, SUJIT GHOSH, and BAILIAN LI. "A blocking Gibbs sampling method to detect major genes with phenotypic data from a diallel mating." Genetical Research 83, no. 2 (2004): 143–54. http://dx.doi.org/10.1017/s0016672304006718.

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Diallel mating is a frequently used design for estimating the additive and dominance genetic (polygenic) effects involved in quantitative traits observed in the half- and full-sib progenies generated in plant breeding programmes. Gibbs sampling has been used for making statistical inferences for a mixed-inheritance model (MIM) that includes both major genes and polygenes. However, using this approach it has not been possible to incorporate the genetic properties of major genes with the additive and dominance polygenic effects in a diallel mating population. A parent block Gibbs sampling method

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Ma, Xiaoman, Weifeng Guo, Liangrong He, and Xinchuan Cao. "Polygenic Genetic Analysis of Principal Genes for Yield Traits in Land Cotton." Agronomy 14, no. 11 (2024): 2749. http://dx.doi.org/10.3390/agronomy14112749.

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Objective: Yield traits are crucial for cotton breeding. Analyzing the yield traits of terrestrial cotton and exploring their genetic mechanisms through a primary gene + multigene hybrid genetic model provide a theoretical basis for selecting high-quality cotton varieties and identifying associated molecular markers. Methods: Completing the construction of the six populations (P1, P2, F1, F2, B1, B2) using Xinluzhong 37 as the female parent and Xinluzhong 51 as the male parent. Six yield traits were assessed: single boll weight, boll number per plant, lint yield per plant, seed cotton per plan

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Crouch, Daniel J. M., and Walter F. Bodmer. "Polygenic inheritance, GWAS, polygenic risk scores, and the search for functional variants." Proceedings of the National Academy of Sciences 117, no. 32 (2020): 18924–33. http://dx.doi.org/10.1073/pnas.2005634117.

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The reconciliation between Mendelian inheritance of discrete traits and the genetically based correlation between relatives for quantitative traits was Fisher’s infinitesimal model of a large number of genetic variants, each with very small effects, whose causal effects could not be individually identified. The development of genome-wide genetic association studies (GWAS) raised the hope that it would be possible to identify single polymorphic variants with identifiable functional effects on complex traits. It soon became clear that, with larger and larger GWAS on more and more complex traits,

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5

Luciano, Michelle, Riccardo E. Marioni, Maria Valdés Hernández, et al. "Structural Brain MRI Trait Polygenic Score Prediction of Cognitive Abilities." Twin Research and Human Genetics 18, no. 6 (2015): 738–45. http://dx.doi.org/10.1017/thg.2015.71.

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Structural brain magnetic resonance imaging (MRI) traits share part of their genetic variance with cognitive traits. Here, we use genetic association results from large meta-analytic studies of genome-wide association (GWA) for brain infarcts (BI), white matter hyperintensities, intracranial, hippocampal, and total brain volumes to estimate polygenic scores for these traits in three Scottish samples: Generation Scotland: Scottish Family Health Study (GS:SFHS), and the Lothian Birth Cohorts of 1936 (LBC1936) and 1921 (LBC1921). These five brain MRI trait polygenic scores were then used to: (1)

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6

Ridenhour, Benjamin J., and Scott L. Nuismer. "POLYGENIC TRAITS AND PARASITE LOCAL ADAPTATION." Evolution 61, no. 2 (2007): 368–76. http://dx.doi.org/10.1111/j.1558-5646.2007.00029.x.

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7

Wright, Fred A., and Augustine Kong. "Linkage Mapping in Experimental Crosses: The Robustness of Single-Gene Models." Genetics 146, no. 1 (1997): 417–25. http://dx.doi.org/10.1093/genetics/146.1.417.

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The robustness of parametric linkage mapping against model misspecification is considered in experimental breeding designs, with a focus on localization of the gene. By examining the expected LOD across the genome, it is shown that single-gene models are quite robust, even for polygenic traits. However, when the marker map is of low resolution, linked polygenes can give rise to an apparent “ghost” gene, mapped to an incorrect interval. The results apply equally well to quantitative traits or qualitative (categorical) traits. The results are derived for backcross populations, with a discussion

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8

Jansen, Ritsert C. "Complex plant traits: Time for polygenic analysis." Trends in Plant Science 1, no. 3 (1996): 89–94. http://dx.doi.org/10.1016/s1360-1385(96)80040-9.

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9

Josephs, Emily B., Jeremy J. Berg, Jeffrey Ross-Ibarra, and Graham Coop. "Detecting Adaptive Differentiation in Structured Populations with Genomic Data and Common Gardens." Genetics 211, no. 3 (2019): 989–1004. http://dx.doi.org/10.1534/genetics.118.301786.

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Adaptation in quantitative traits often occurs through subtle shifts in allele frequencies at many loci—a process called polygenic adaptation. While a number of methods have been developed to detect polygenic adaptation in human populations, we lack clear strategies for doing so in many other systems. In particular, there is an opportunity to develop new methods that leverage datasets with genomic data and common garden trait measurements to systematically detect the quantitative traits important for adaptation. Here, we develop methods that do just this, using principal components of the rela

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10

Rosenberg, Noah A., Michael D. Edge, Jonathan K. Pritchard, and Marcus W. Feldman. "Interpreting polygenic scores, polygenic adaptation, and human phenotypic differences." Evolution, Medicine, and Public Health 2019, no. 1 (2018): 26–34. http://dx.doi.org/10.1093/emph/eoy036.

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Abstract Recent analyses of polygenic scores have opened new discussions concerning the genetic basis and evolutionary significance of differences among populations in distributions of phenotypes. Here, we highlight limitations in research on polygenic scores, polygenic adaptation and population differences. We show how genetic contributions to traits, as estimated by polygenic scores, combine with environmental contributions so that differences among populations in trait distributions need not reflect corresponding differences in genetic propensity. Under a null model in which phenotypes are

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11

Hirtz, Raphael, and Anke Hinney. "Genetic and epigenetic findings in anorexia nervosa." Medizinische Genetik 32, no. 1 (2020): 25–29. http://dx.doi.org/10.1515/medgen-2020-2005.

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Abstract Polygenic factors are relevant for the genetic predispositions to the eating disorder anorexia nervosa (AN). The most recent genome-wide association study (GWAS) for AN comprised almost 17,000 patients with AN and controls. A total of eight genome-wide significant polygenic loci associated with AN have been identified. Each single polygenic locus makes only a small contribution to the development of AN. Analyses across different traits successfully identified regions/genes for AN that had not been detected by analyses of the single traits. Functional studies of the genes derived by GW

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12

Sun, Quan, Jiawen Du, Yihan Tang, et al. "Polygenic Scores of Cardiometabolic Risk Factors in American Indian Adults." JAMA Network Open 8, no. 3 (2025): e250535. https://doi.org/10.1001/jamanetworkopen.2025.0535.

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ImportanceNumerous efforts have been made to include diverse populations in genetic studies, but American Indian populations are still severely underrepresented. Polygenic scores derived from genetic data have been proposed in clinical care, but how polygenic scores perform in American Indian individuals and whether they can predict disease risk in this population remains unknown.ObjectiveTo study the performance of polygenic scores for cardiometabolic risk factors of lipid traits and C-reactive protein in American Indian adults and to determine whether such scores are helpful in clinical pred

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13

Chande, Aroon T., Lu Wang, Lavanya Rishishwar, et al. "GlobAl Distribution of GEnetic Traits (GADGET) web server: polygenic trait scores worldwide." Nucleic Acids Research 46, W1 (2018): W121—W126. http://dx.doi.org/10.1093/nar/gky415.

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14

Weir, Bruce S. "Bioinformatics and Approaches to Identifying Polygenic Susceptibility Traits." Annals of Periodontology 7, no. 1 (2002): 1–7. http://dx.doi.org/10.1902/annals.2002.7.1.1.

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15

Weeks, Daniel E., and G. Mark Lathrop. "Polygenic disease: methods for mapping complex disease traits." Trends in Genetics 11, no. 12 (1995): 513–19. http://dx.doi.org/10.1016/s0168-9525(00)89163-5.

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16

Chakraborty, Ranajit. "Biochemical heterozygosity and phenotypic variability of polygenic traits." Heredity 59, no. 1 (1987): 19–28. http://dx.doi.org/10.1038/hdy.1987.92.

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17

Avner, Philip. "Complex Traits and Polygenic Inheritance in the Mouse." Methods 14, no. 2 (1998): 191–98. http://dx.doi.org/10.1006/meth.1997.0577.

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18

Docherty, Anna R., Arden Moscati, Danielle Dick, et al. "Polygenic prediction of the phenome, across ancestry, in emerging adulthood." Psychological Medicine 48, no. 11 (2017): 1814–23. http://dx.doi.org/10.1017/s0033291717003312.

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AbstractBackgroundIdentifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on the clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.MethodsThis study examined a sample of emerging adults 18–22 years of age (N = 5947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. Twenty-eight hypotheses were tested based on t

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19

Richardson, Tom G., Katie O’Nunain, Caroline L. Relton, and George Davey Smith. "Harnessing Whole Genome Polygenic Risk Scores to Stratify Individuals Based on Cardiometabolic Risk Factors and Biomarkers at Age 10 in the Lifecourse—Brief Report." Arteriosclerosis, Thrombosis, and Vascular Biology 42, no. 3 (2022): 362–65. http://dx.doi.org/10.1161/atvbaha.121.316650.

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Background: In this study, we investigated the capability of polygenic risk scores to stratify a cohort of young individuals into risk deciles based on 10 different cardiovascular traits and circulating biomarkers. Methods: We first conducted large-scale genome-wide association studies using data on adults (mean age 56.5 years) enrolled in the UK Biobank study (n=393 193 to n=461 460). Traits and biomarkers analyzed were body mass index, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, apolipoprotein B,

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20

ZHAO, JING, DALIA ARAFAT, KENNETH L. BRIGHAM, and GREG GIBSON. "Genetic risk prediction in a small cohort of healthy adults in Atlanta." Genetics Research 95, no. 1 (2013): 30–37. http://dx.doi.org/10.1017/s0016672313000025.

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SummaryCompared with single markers, polygenic scores that evaluate the joint effects of multiple trait-associated variants are more effective in explaining the variance of traits and risk of diseases. In total, 182 CHDWB (Emory-Georgia Tech Center for Health Discovery and Well Being study) adults were genotyped to investigate the common variant contributions to three traits (height, BMI, serum triglycerides) and three diseases (coronary artery disease (CAD), type 2 diabetes (T2D) and asthma). Association was contrasted between weighted and simple allelic sum polygenic scores with quantitative

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21

Weiss, Alexander, Bart M. L. Baselmans, Edith Hofer, et al. "Personality Polygenes, Positive Affect, and Life Satisfaction." Twin Research and Human Genetics 19, no. 5 (2016): 407–17. http://dx.doi.org/10.1017/thg.2016.65.

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Approximately half of the variation in wellbeing measures overlaps with variation in personality traits. Studies of non-human primate pedigrees and human twins suggest that this is due to common genetic influences. We tested whether personality polygenic scores for the NEO Five-Factor Inventory (NEO-FFI) domains and for item response theory (IRT) derived extraversion and neuroticism scores predict variance in wellbeing measures. Polygenic scores were based on published genome-wide association (GWA) results in over 17,000 individuals for the NEO-FFI and in over 63,000 for the IRT extraversion a

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22

Ma, Yujia, Zechen Zhou, Xiaoyi Li, et al. "Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes." Biomedicines 10, no. 2 (2022): 368. http://dx.doi.org/10.3390/biomedicines10020368.

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Accumulating evidence suggests a relationship between type 2 diabetes mellitus and sleep problems. A comprehensive study is needed to decipher whether shared polygenic risk variants exist between diabetic traits and sleep traits. Methods: We integrated summary statistics from different genome-wide association studies and investigated overlap in single-nucleotide polymorphisms (SNPs) associated with diabetes-related traits (type 2 diabetes, fasting glucose, fasting insulin, and glycated hemoglobin) and sleep traits (insomnia symptoms, sleep duration, and chronotype) using a conditional/conjunct

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23

ILAHI, H., E. MANFREDI, P. CHASTIN, F. MONOD, J. M. ELSEN, and P. LE ROY. "Genetic variability in milking speed of dairy goats." Genetical Research 75, no. 3 (2000): 315–19. http://dx.doi.org/10.1017/s001667230000450x.

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The present investigation deals with the genetic variability of milking speed, measured as the volume of milk collected during the first minute of milking (MD1), and its association with dairy traits. Data originated from 2589 lactations of 1421 Alpine goats, sired by 93 bucks, measured between 1985 and 1997 at the Moissac Goat Experimental Station (Lozère, France). Two genetic analyses were carried out. Firstly, a polygenic model was used to estimate genetic and phenotypic parameters among milking speed and dairy traits using a multiple-trait animal model. Secondly, segregation analysis was u

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Mironov, Alexey, Anastasia Zastavnyuk, Nikolay Mokhov, Yulia Degtyareva, and Victoria Kulagina. "Genetics of Cucumber (Cucumis sativus) traits." АгроЭкоИнфо 4, no. 52 (2022): 2. http://dx.doi.org/10.51419/202124402.

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The analysis of literary sources for the presence of monogenic, oligo and polygenic traits of cucumber (Cucumis sativus) was carried out. Valuable crop diseases include high yield, genetic absence of fruit bitterness, evenness, as well as cases of biotic and abiotic diseases. Keywords: CUCUMBER, GENE, TRAIT GENETICS

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25

Plomin, Robert, and Sophie von Stumm. "Polygenic scores: prediction versus explanation." Molecular Psychiatry 27, no. 1 (2021): 49–52. http://dx.doi.org/10.1038/s41380-021-01348-y.

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AbstractDuring the past decade, polygenic scores have become a fast-growing area of research in the behavioural sciences. The ability to directly assess people’s genetic propensities has transformed research by making it possible to add genetic predictors of traits to any study. The value of polygenic scores in the behavioural sciences rests on using inherited DNA differences to predict, from birth, common disorders and complex traits in unrelated individuals in the population. This predictive power of polygenic scores does not require knowing anything about the processes that lie between gene

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Kuzhir, Tat'yana D. "The polygenic nature of rheumatoid arthritis." Ecological genetics 17, no. 4 (2019): 77–90. http://dx.doi.org/10.17816/ecogen17477-90.

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Current advances in the genetic basis of rheumatoid arthritis (RA) were summarized in the review. Influence of gene polymorphisms involved in different cellular processes including cytokine-mediated signal transduction, immune and inflammatory responses to exogenous stimuli was discussed. The principal role of the major histocompatibility complex (MHC) and a shared epitope (SE), as well as contribution of non-HLA genes to susceptibility to RA was considered in terms of patients ethnicity and the serological status for the disease. The GWAS results for revealing candidate genes closely associat

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27

Lvovs, D., O. O. Favorova, and A. V. Favorov. "A Polygenic Approach to the Study of Polygenic Diseases." Acta Naturae 4, no. 3 (2012): 59–71. http://dx.doi.org/10.32607/20758251-2012-4-3-59-71.

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Polygenic diseases are caused by the joint contribution of a number of independently acting or interacting polymorphic genes; the individual contribution of each gene may be small or even unnoticeable. The carriage of certain combinations of genes can determine the occurrence of clinically heterogeneous forms of the disease and treatment efficacy. This review describes the approaches used in a polygenic analysis of data in medical genomics, in particular, pharmacogenomics, aimed at identifying the cumulative effect of genes. This effect may result from the summation of gains of different genes

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Siemens, Angela, Spencer J. Anderson, S. Rod Rassekh, Colin J. D. Ross, and Bruce C. Carleton. "A Systematic Review of Polygenic Models for Predicting Drug Outcomes." Journal of Personalized Medicine 12, no. 9 (2022): 1394. http://dx.doi.org/10.3390/jpm12091394.

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Polygenic models have emerged as promising prediction tools for the prediction of complex traits. Currently, the majority of polygenic models are developed in the context of predicting disease risk, but polygenic models may also prove useful in predicting drug outcomes. This study sought to understand how polygenic models incorporating pharmacogenetic variants are being used in the prediction of drug outcomes. A systematic review was conducted with the aim of gaining insights into the methods used to construct polygenic models, as well as their performance in drug outcome prediction. The searc

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Chen, Jingchun, Travis Mize, Jain-Shing Wu, et al. "Polygenic Risk Scores for Subtyping of Schizophrenia." Schizophrenia Research and Treatment 2020 (July 24, 2020): 1–13. http://dx.doi.org/10.1155/2020/1638403.

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Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) from schizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, we found a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for the patients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found in the MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters

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Mõttus, René, Anu Realo, Uku Vainik, Jüri Allik, and Tõnu Esko. "Educational Attainment and Personality Are Genetically Intertwined." Psychological Science 28, no. 11 (2017): 1631–39. http://dx.doi.org/10.1177/0956797617719083.

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Heritable variance in psychological traits may reflect genetic and biological processes that are not necessarily specific to these particular traits but pertain to a broader range of phenotypes. We tested the possibility that the personality domains of the five-factor model and their 30 facets, as rated by people themselves and their knowledgeable informants, reflect polygenic influences that have been previously associated with educational attainment. In a sample of more than 3,000 adult Estonians, education polygenic scores (EPSs), which are interpretable as estimates of molecular-genetic pr

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Crone, Bradley, and Alan P. Boyle. "Enhancing portability of trans-ancestral polygenic risk scores through tissue-specific functional genomic data integration." PLOS Genetics 20, no. 8 (2024): e1011356. http://dx.doi.org/10.1371/journal.pgen.1011356.

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Portability of trans-ancestral polygenic risk scores is often confounded by differences in linkage disequilibrium and genetic architecture between ancestries. Recent literature has shown that prioritizing GWAS SNPs with functional genomic evidence over strong association signals can improve model portability. We leveraged three RegulomeDB-derived functional regulatory annotations—SURF, TURF, and TLand—to construct polygenic risk models across a set of quantitative and binary traits highlighting functional mutations tagged by trait-associated tissue annotations. Tissue-specific prioritization b

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Barton, N. H., and H. P. de Vladar. "Statistical Mechanics and the Evolution of Polygenic Quantitative Traits." Genetics 181, no. 3 (2008): 997–1011. http://dx.doi.org/10.1534/genetics.108.099309.

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Aslam Chow, Muhammad, Ashi Ambreen ., and Ihsan Khaliq . "Genetic Control of Some Polygenic Traits in Aestivum Species." Asian Journal of Plant Sciences 1, no. 3 (2002): 235–37. http://dx.doi.org/10.3923/ajps.2002.235.237.

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34

Mathieson, Iain. "The omnigenic model and polygenic prediction of complex traits." American Journal of Human Genetics 108, no. 9 (2021): 1558–63. http://dx.doi.org/10.1016/j.ajhg.2021.07.003.

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35

Song, Weichen, Yueqi Shi, Weidi Wang, et al. "A selection pressure landscape for 870 human polygenic traits." Nature Human Behaviour 5, no. 12 (2021): 1731–43. http://dx.doi.org/10.1038/s41562-021-01231-4.

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36

Karavani, Ehud, Or Zuk, Danny Zeevi, et al. "Screening Human Embryos for Polygenic Traits Has Limited Utility." Cell 179, no. 6 (2019): 1424–35. http://dx.doi.org/10.1016/j.cell.2019.10.033.

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37

Rao, Madhumathi. "Cardiovascular and Kidney Disease Traits—Pleiotropic or Just Polygenic?" American Journal of Kidney Diseases 61, no. 6 (2013): 851–54. http://dx.doi.org/10.1053/j.ajkd.2013.03.007.

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Cox, T. S., D. J. Cox, and K. J. Frey. "Mutations for polygenic traits in barley under nutrient stress." Euphytica 36, no. 3 (1987): 823–29. http://dx.doi.org/10.1007/bf00051866.

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Priyanka, S., R. Sudhagar, C. Vanniarajan, K. Ganesamurthy, and J. Souframanien. "Induction of genetic variability for quantitative traits in horsegram (Macrotyloma uniflorum) through irradiation mutagenesis." Journal of Environmental Biology 42, no. 3 (2021): 597–608. http://dx.doi.org/10.22438/jeb/42/3/mrn-1491.

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Aim: The study was conducted to explore the magnitude of variability induced by gamma rays, electron beam and its combinations for quantitative traits in horsegram (Macrotyloma uniflorum (Lam) Verdc.). Methodology: The horsegram cultivar PAIYUR 2 was irradiated with twelve combinations involving G, EB and G+EB. Desirable mutagenic doses were identified in M1 based on plant injuries and forwarded to M2. Data on 11 yield component traits were recorded on normal looking M2 plants for identification of micro-mutants. Promising mutants were forwarded to M3 and the induced variability was ascertaine

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40

Hartfield, Matthew, and Sylvain Glémin. "Polygenic selection to a changing optimum under self–fertilisation." PLOS Genetics 20, no. 7 (2024): e1011312. http://dx.doi.org/10.1371/journal.pgen.1011312.

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Many traits are polygenic, affected by multiple genetic variants throughout the genome. Selection acting on these traits involves co–ordinated allele–frequency changes at these underlying variants, and this process has been extensively studied in random–mating populations. Yet many species self–fertilise to some degree, which incurs changes to genetic diversity, recombination and genome segregation. These factors cumulatively influence how polygenic selection is realised in nature. Here, we use analytical modelling and stochastic simulations to investigate to what extent self–fertilisation aff

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Mackay, Trudy F. C. "Transposable element-induced polygenic mutations in Drosophila melanogaster." Genetical Research 49, no. 3 (1987): 225–33. http://dx.doi.org/10.1017/s0016672300027117.

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SummaryP-element mutagenesis was used to contaminate M-strain second chromosomes with P elements. The effect of P-element transposition on abdominal and sternopleural bristle scores and on female productivity was deduced by comparing the distributions of these quantitative traits among the contaminated second-chromosome lines with a control population of M-strain second-chromosome lines free of P elements. Estimates of P-element-induced mutational variance, Vm, for these characters are very high, and mutational ‘heritabilities’ (Vm/Ve, the ratio of mutational variance to environmental variance

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Rowan, Troy N., Harly J. Durbin, Christopher M. Seabury, Robert D. Schnabel, and Jared E. Decker. "Powerful detection of polygenic selection and evidence of environmental adaptation in US beef cattle." PLOS Genetics 17, no. 7 (2021): e1009652. http://dx.doi.org/10.1371/journal.pgen.1009652.

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Selection on complex traits can rapidly drive evolution, especially in stressful environments. This polygenic selection does not leave intense sweep signatures on the genome, rather many loci experience small allele frequency shifts, resulting in large cumulative phenotypic changes. Directional selection and local adaptation are changing populations; but, identifying loci underlying polygenic or environmental selection has been difficult. We use genomic data on tens of thousands of cattle from three populations, distributed over time and landscapes, in linear mixed models with novel dependent

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43

Ou, Jen-Hsiang, Tilman Rönneburg, Örjan Carlborg, Christa Ferst Honaker, Paul B. Siegel, and Carl-Johan Rubin. "Complex genetic architecture of the chicken Growth1 QTL region." PLOS ONE 19, no. 5 (2024): e0295109. http://dx.doi.org/10.1371/journal.pone.0295109.

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The genetic complexity of polygenic traits represents a captivating and intricate facet of biological inheritance. Unlike Mendelian traits controlled by a single gene, polygenic traits are influenced by multiple genetic loci, each exerting a modest effect on the trait. This cumulative impact of numerous genes, interactions among them, environmental factors, and epigenetic modifications results in a multifaceted architecture of genetic contributions to complex traits. Given the well-characterized genome, diverse traits, and range of genetic resources, chicken (Gallus gallus) was employed as a m

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Keightley, Peter D., and Ohmi Ohnishi. "EMS-Induced Polygenic Mutation Rates for Nine Quantitative Characters in Drosophila melanogaster." Genetics 148, no. 2 (1998): 753–66. http://dx.doi.org/10.1093/genetics/148.2.753.

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Abstract Polygenic mutations were induced by treating Drosophila melanogaster adult males with 2.5 mm EMS. The treated second chromosomes, along with untreated controls, were then made homozygous, and five life history, two behavioral, and two morphological traits were measured. EMS mutagenesis led to reduced performance for life history traits. Changes in means and increments in genetic variance were relatively much higher for life history than for morphological traits, implying large differences in mutational target size. Maximum likelihood was used to estimate mutation rates and parameters

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45

Thaller, G., L. Dempfle, and I. Hoeschele. "Maximum Likelihood Analysis of Rare Binary Traits Under Different Modes of Inheritance." Genetics 143, no. 4 (1996): 1819–29. http://dx.doi.org/10.1093/genetics/143.4.1819.

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Abstract Maximum likelihood methodology was applied to determine the mode of inheritance of rare binary traits with data structures typical for swine populations. The genetic models considered included a monogenic, a digenic, a polygenic, and three mixed polygenic and major gene models. The main emphasis was on the detection of major genes acting on a polygenic background. Deterministic algorithms were employed to integrate and maximize likelihoods. A simulation study was conducted to evaluate model selection and parameter estimation. Three designs were simulated that differed in the number of

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Giel, Ann-Sophie, Jessica Bigge, Johannes Schumacher, Carlo Maj, and Pouria Dasmeh. "Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity in Traits Across Polygenic Phenotypes." Molecular Biology and Evolution, June 12, 2024. http://dx.doi.org/10.1093/molbev/msae115.

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Abstract Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exh

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Mahmoud, Medhat, Mila Tost, Ngoc-Thuy Ha, Henner Simianer, and Timothy Beissinger. "Ghat: An R package for identifying adaptive polygenic traits." G3 Genes|Genomes|Genetics, December 1, 2022. http://dx.doi.org/10.1093/g3journal/jkac319.

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Abstract Identifying selection on polygenic complex traits in crops and livestock is important for understanding evolution and helps prioritize important characteristics for breeding. QTL that contribute to polygenic trait variation often exhibit small or infinitesimal effects. This hinders the ability to detect QTL controlling polygenic traits because enormously high statistical power is needed for their detection. Recently, we circumvented this challenge by introducing a method to identify selection on complex traits by evaluating the relationship between genome-wide changes in allele freque

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Otsuka, Ikuo, Hanga Galfalvy, Jia Guo, et al. "Mapping the genetic architecture of suicide attempt and suicide death using polygenic risk scores for clinically-related psychiatric disorders and traits." Psychological Medicine, November 18, 2021, 1–9. http://dx.doi.org/10.1017/s0033291721004700.

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Abstract Background Suicidal behavior is moderately heritable and a consequence of a combination of the diathesis traits for suicidal behavior and suicide-related major psychiatric disorders. Here, we sought to examine shared polygenic effects between various psychiatric disorders/traits and suicidal behavior and to compare the shared polygenic effects of various psychiatric disorders/traits on non-fatal suicide attempt and suicide death. Methods We used our genotyped European ancestry sample of 260 non-fatal suicide attempters, 317 suicide decedents and 874 non-psychiatric controls to test wh

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Riehl, Jennifer F. L., Christopher T. Cole, Clay J. Morrow, et al. "Genomic and transcriptomic analyses reveal polygenic architecture for ecologically important traits in aspen (Populus tremuloides Michx.)." Ecology and Evolution 13, no. 10 (2023). http://dx.doi.org/10.1002/ece3.10541.

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AbstractIntraspecific genetic variation in foundation species such as aspen (Populus tremuloides Michx.) shapes their impact on forest structure and function. Identifying genes underlying ecologically important traits is key to understanding that impact. Previous studies, using single‐locus genome‐wide association (GWA) analyses to identify candidate genes, have identified fewer genes than anticipated for highly heritable quantitative traits. Mounting evidence suggests that polygenic control of quantitative traits is largely responsible for this “missing heritability” phenomenon. Our research

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Pingault, Jean-Baptiste, Wikus Barkhuizen, Biyao Wang, et al. "Genetic nurture versus genetic transmission of risk for ADHD traits in the Norwegian Mother, Father and Child Cohort Study." Molecular Psychiatry, November 16, 2022. http://dx.doi.org/10.1038/s41380-022-01863-6.

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AbstractIdentifying mechanisms underlying the intergenerational transmission of risk for attention-deficit/hyperactivity disorder (ADHD) traits can inform interventions and provide insights into the role of parents in shaping their children’s outcomes. We investigated whether genetic transmission and genetic nurture (environmentally mediated effects) underlie associations between polygenic scores indexing parental risk and protective factors and their offspring’s ADHD traits. This birth cohort study included 19,506 genotyped mother-father-offspring trios from the Norwegian Mother, Father and C

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