Gene-to-phenotype models and complex trait genetics

2005 ◽  
Vol 56 (9) ◽  
pp. 895 ◽  
Author(s):  
Mark Cooper ◽  
Dean W. Podlich ◽  
Oscar S. Smith
Keyword(s):  
Quantitative Genetics ◽  
Complex Traits ◽  
Molecular Breeding ◽  
Complex Trait ◽  
Theoretical Framework ◽  
Breeding Strategies ◽  
Gene Effects ◽  
Gene Environment ◽  
Starting Point ◽  
Context Dependent

The premise that is explored in this paper is that in some cases, in order to make progress in the design of molecular breeding strategies for complex traits, we will need a theoretical framework for quantitative genetics that is grounded in the concept of gene-networks. We seek to develop a gene-to-phenotype (G→P) modelling framework for quantitative genetics that explicitly deals with the context-dependent gene effects that are attributed to genes functioning within networks, i.e. epistasis, gene × environment interactions, and pleiotropy. The E(NK) model is discussed as a starting point for building such a theoretical framework for complex trait genetics. Applying this framework to a combination of theoretical and empirical G→P models, we find that although many of the context-dependent effects of genetic variation on phenotypic variation can reduce the rate of genetic progress from breeding, it is possible to design molecular breeding strategies for complex traits that on average will outperform phenotypic selection. However, to realise these potential advantages, empirical G→P models of the traits will need to take into consideration the context-dependent effects that are a consequence of epistasis, gene × environment interactions, and pleiotropy. Some promising G→P modelling directions are discussed.

Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

2005 ◽  
Vol 56 (9) ◽  
pp. 947 ◽  
Author(s):  
Graeme L. Hammer ◽  
Scott Chapman ◽  
Erik van Oosterom ◽  
Dean W. Podlich
Keyword(s):  
Complex Traits ◽  
Crop Improvement ◽  
Target Population ◽  
Breeding Strategies ◽  
Stay Green ◽  
Gene Effects ◽  
Component Trait ◽  
Phenotypic Complexity ◽  
Eastern Australia ◽  
Genetic Systems

New tools derived from advances in molecular biology have not been widely adopted in plant breeding for complex traits because of the inability to connect information at gene level to the phenotype in a manner that is useful for selection. In this study, we explored whether physiological dissection and integrative modelling of complex traits could link phenotype complexity to underlying genetic systems in a way that enhanced the power of molecular breeding strategies. A crop and breeding system simulation study on sorghum, which involved variation in 4 key adaptive traits—phenology, osmotic adjustment, transpiration efficiency, stay-green—and a broad range of production environments in north-eastern Australia, was used. The full matrix of simulated phenotypes, which consisted of 547 location–season combinations and 4235 genotypic expression states, was analysed for genetic and environmental effects. The analysis was conducted in stages assuming gradually increased understanding of gene-to-phenotype relationships, which would arise from physiological dissection and modelling. It was found that environmental characterisation and physiological knowledge helped to explain and unravel gene and environment context dependencies in the data. Based on the analyses of gene effects, a range of marker-assisted selection breeding strategies was simulated. It was shown that the inclusion of knowledge resulting from trait physiology and modelling generated an enhanced rate of yield advance over cycles of selection. This occurred because the knowledge associated with component trait physiology and extrapolation to the target population of environments by modelling removed confounding effects associated with environment and gene context dependencies for the markers used. Developing and implementing this gene-to-phenotype capability in crop improvement requires enhanced attention to phenotyping, ecophysiological modelling, and validation studies to test the stability of candidate genetic regions.

Evolution and Selection of Quantitative Traits

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Mathematical Models ◽  
Quantitative Genetics ◽  
Complex Traits ◽  
Evolutionary Biology ◽  
Quantitative Traits ◽  
Specific Gene ◽  
Real World Data ◽  
Holistic Treatment ◽  
Genetics And Genomics ◽  
Selection Of

Quantitative traits—be they morphological or physiological characters, aspects of behavior, or genome-level features such as the amount of RNA or protein expression for a specific gene—usually show considerable variation within and among populations. Quantitative genetics, also referred to as the genetics of complex traits, is the study of such characters and is based on mathematical models of evolution in which many genes influence the trait and in which non-genetic factors may also be important. Evolution and Selection of Quantitative Traits presents a holistic treatment of the subject, showing the interplay between theory and data with extensive discussions on statistical issues relating to the estimation of the biologically relevant parameters for these models. Quantitative genetics is viewed as the bridge between complex mathematical models of trait evolution and real-world data, and the authors have clearly framed their treatment as such. This is the second volume in a planned trilogy that summarizes the modern field of quantitative genetics, informed by empirical observations from wide-ranging fields (agriculture, evolution, ecology, and human biology) as well as population genetics, statistical theory, mathematical modeling, genetics, and genomics. Whilst volume 1 (1998) dealt with the genetics of such traits, the main focus of volume 2 is on their evolution, with a special emphasis on detecting selection (ranging from the use of genomic and historical data through to ecological field data) and examining its consequences. This extensive work of reference is suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of evolutionary biology, genetics, and genomics. It will also be of particular relevance and use to plant and animal breeders, human geneticists, and statisticians.

scholarly journals Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chao-Yu Guo ◽  
Reng-Hong Wang ◽  
Hsin-Chou Yang
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Association Test ◽  
Whole Genome Sequence ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequence Kernel Association Test ◽  
Gene Environment ◽  
Family Based

AbstractAfter the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.

scholarly journals The Candidate Genes Underlying a Stably Expressed QTL for Low Temperature Germinability in Rice (Oryza sativa L.)

Rice ◽  
2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Tifeng Yang ◽  
Lian Zhou ◽  
Junliang Zhao ◽  
Jingfang Dong ◽  
Qing Liu ◽  
...  
Keyword(s):  
Low Temperature ◽  
Differential Expression ◽  
Candidate Genes ◽  
Complex Traits ◽  
Molecular Breeding ◽  
Genome Wide Association Study ◽  
Oryza Sativa L ◽  
Sequence Comparisons ◽  
Cold Environments ◽  
Promising Source

Abstract Background Direct seeding is an efficient cultivation technique in rice. However, poor low temperature germinability (LTG) of modern rice cultivars limits its application. Identifying the genes associated with LTG and performing molecular breeding is the fundamental way to address this issue. However, few LTG QTLs have been fine mapped and cloned so far. Results In the present study, the LTG evaluation of 375 rice accessions selected from the Rice Diversity Panel 2 showed that there were large LTG variations within the population, and the LTG of Indica group was significantly higher than that of Japonica and Aus groups (p < 0.01). In total, eleven QTLs for LTG were identified through genome-wide association study (GWAS). Among them, qLTG_sRDP2–3/qLTG_JAP-3, qLTG_AUS-3 and qLTG_sRDP2–12 are first reported in the present study. The QTL on chromosome 10, qLTG_sRDP2–10a had the largest contribution to LTG variations in 375 rice accessions, and was further validated using single segment substitution line (SSSL). The presence of qLTG_sRDP2–10a could result in 59.8% increase in LTG under 15 °C low temperature. The expression analysis of the genes within qLTG_sRDP2–10a region indicated that LOC_Os10g22520 and LOC_Os10g22484 exhibited differential expression between the high and low LTG lines. Further sequence comparisons revealed that there were insertion and deletion sequence differences in the promoter and intron region of LOC_Os10g22520, and an about 6 kb variation at the 3′ end of LOC_Os10g22484 between the high and low LTG lines, suggesting that the sequence variations of the two genes could be the cause for their differential expression in high and low LTG lines. Conclusion Among the 11 QTLs identified in this study, qLTG_sRDP2–10a could also be detected in other three studies using different germplasm under different cold environments. Its large effect and stable expression make qLTG_sRDP2–10a particularly valuable in rice breeding. The two genes, LOC_Os10g22484 and LOC_Os10g22520, were considered as the candidate genes underlying qLTG_sRDP2–10a. Our results suggest that integrating GWAS and SSSL can facilitate identification of QTL for complex traits in rice. The identification of qLTG_sRDP2–10a and its candidate genes provide a promising source for gene cloning of LTG and molecular breeding for LTG in rice.

scholarly journals Leveraging Multiple Layers of Data To Predict Drosophila Complex Traits

2020 ◽  
Vol 10 (12) ◽  
pp. 4599-4613
Author(s):  
Fabio Morgante ◽  
Wen Huang ◽  
Peter Sørensen ◽  
Christian Maltecca ◽  
Trudy F. C. Mackay
Keyword(s):  
Precision Agriculture ◽  
Complex Traits ◽  
Prediction Accuracy ◽  
Cellular Response ◽  
Complex Trait ◽  
Sources Of Information ◽  
Starvation Resistance ◽  
Expression Levels ◽  
Chill Coma ◽  
Additional Layer

The ability to accurately predict complex trait phenotypes from genetic and genomic data are critical for the implementation of personalized medicine and precision agriculture; however, prediction accuracy for most complex traits is currently low. Here, we used data on whole genome sequences, deep RNA sequencing, and high quality phenotypes for three quantitative traits in the ∼200 inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) to compare the prediction accuracies of gene expression and genotypes for three complex traits. We found that expression levels (r = 0.28 and 0.38, for females and males, respectively) provided higher prediction accuracy than genotypes (r = 0.07 and 0.15, for females and males, respectively) for starvation resistance, similar prediction accuracy for chill coma recovery (null for both models and sexes), and lower prediction accuracy for startle response (r = 0.15 and 0.14 for female and male genotypes, respectively; and r = 0.12 and 0.11, for females and male transcripts, respectively). Models including both genotype and expression levels did not outperform the best single component model. However, accuracy increased considerably for all the three traits when we included gene ontology (GO) category as an additional layer of information for both genomic variants and transcripts. We found strongly predictive GO terms for each of the three traits, some of which had a clear plausible biological interpretation. For example, for starvation resistance in females, GO:0033500 (r = 0.39 for transcripts) and GO:0032870 (r = 0.40 for transcripts), have been implicated in carbohydrate homeostasis and cellular response to hormone stimulus (including the insulin receptor signaling pathway), respectively. In summary, this study shows that integrating different sources of information improved prediction accuracy and helped elucidate the genetic architecture of three Drosophila complex phenotypes.

Algorithmenkompatibles Verwaltungsrecht?

2021 ◽  
Vol 54 (2) ◽  
pp. 251-272
Author(s):  
Margrit Seckelmann
Keyword(s):  
Computer Code ◽  
Administrative Law ◽  
Context Dependency ◽  
New Paradigm ◽  
Starting Point ◽  
Context Dependent ◽  
Legal Meaning ◽  
Automatic Decisions

Die Übersetzung von Recht in (Computer–)‌Code ist derzeit in aller Munde. Lawrence Lessigs berühmtes Diktum, „Code is Law“ wird neuerdings dahingehend reformuliert, dass „Law“ auch „Code“ sei, dass man bei der Rechtsetzung also zugleich seine rechentechnische Umsetzbarkeit mitzudenken habe. Einen Ansatzpunkt für eine derartige „Algorithmisierbarkeit“ von Recht bietet § 35a des Verwaltungsverfahrensgesetzes des Bundes, wonach „automatisierte“ Entscheidungen in bestimmten Fällen zugelassen werden. Ein aktuelles Papier des Fraunhofer FOKUS-Instituts unter dem Titel „Recht Digital“ denkt dieses weiter und suggeriert, man müsse nur die passenden, eindeutigen Ausdrücke finden, dann sei Recht gleichsam „programmierbar“. Aber genau hier stellt sich das Problem: Rechtssprache ist eine Multi-Adressaten-Sprache, also eine Sprache, die sich ebenso sehr an ein Fachpublikum wie an Laien (Bürgerinnen und Bürger) wendet. Sie ist zudem kontextabhängig. Der aktuelle Hype um den Begriff der „Algorithmisierung“ von Gesetzen verbirgt zudem, dass es sich hierbei um ein Grundproblem von Rechtssprache handelt, das in den 1960er bis 1980er Jahren unter den Paradigmata „Rechts-/Verwaltungsautomation“ oder Rechtskybernetik verhandelt wurde. Wie kann man sich also dem Problem der Kontextabhängigkeit von Recht unter dem neuen Paradigma der Algorithmisierung nähern? Im Beitrag über „Algorithmenkompatibles Verwaltungsrecht? Juristische und sprachwissenschaftliche Überlegungen zu einer ‚Standardisierung von Rechtsbegriffen‘“ werden verschiedene Zugänge zur Schaffung einer „algorithmenkonformen“ Rechtssprache vorgestellt. Letztlich aber vermögen es noch so ausgefeilte technische Methoden nicht, das Problem demokratischer Deliberation zu verdrängen – über die fundamentalen Fragen einer Algorithmisierung der Rechtssprache muss der unmittelbar demokratisch legitimierte Gesetzgeber entscheiden. „Kontext“ und „Text“ geraten insoweit in ein wechselseitiges Abhängigkeitsverhältnis. The translation of law into (computer) code seems to be currently on everyone’s lips. Lawrence Lessigs’ famous dictum “Code is Law” has recently been rephrased saying that “Law” was also “Code”. This means that the wording of laws should directly take their “computer implementability” into consideration. A starting point for those postulations can be seen in the (relatively) new section 35a of the (Federal) Administrative Prodecure Act (Verwaltungsverfahrensgesetz), which allows “automatic” decisions in specific cases. A new paper of the Fraunhofer FOKUS institute takes this up and suggests that we have only to look for the appropriate, unambiguous term that corresponds with an unequivocal legal meaning. In doing so, law could be programmable. But this is exactly the point where the problem arises: laws have more than one addressee; they address lawyers as well as citizens (mostly laypeople). Furthermore, legal terminology is context dependent. The current hype regarding the “algorithmization” of legal terminology also hides the fact that this issue was – more or less – discussed once before under the paradigm “legal cybernetics” between 1960 and 1985. So how can we approach the problem of context-dependency of law under the new paradigm of algorithmization? In our contribution on “Algorithm-compatible administrative law? Legal and linguistic considerations concerning the ‘standardization’ of legal terminology”, we will introduce different approaches to safeguard the compatibility of law with computer technics. But how sophisticated a technical method can be: It is the democratically legitimised parliament that must make the fundamental decisions when it comes to an “algorithmization” of legal terminology, because there is no text without context.

scholarly journals Polygenic interactions with environmental adversity in the aetiology of major depressive disorder

2015 ◽  
Vol 46 (4) ◽  
pp. 759-770 ◽  
Author(s):  
N. Mullins ◽  
R. A. Power ◽  
H. L. Fisher ◽  
K. B. Hanscombe ◽  
J. Euesden ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Environmental Risk ◽  
Complex Traits ◽  
Risk Scores ◽  
Environment Interaction ◽  
Inverse Association ◽  
Major Depressive ◽  
Polygenic Risk ◽  
Gene Environment

BackgroundMajor depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene–environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD.MethodThe RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them.ResultsPRS significantly predicted depression, explaining 1.1% of variance in phenotype (p= 1.9 × 10−6). SLEs and CT were also associated with MDD status (p= 2.19 × 10−4andp= 5.12 × 10−20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p= 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples.ConclusionsCT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene–environment interactions in complex traits.

scholarly journals {Tener/llevar} + participio en el castellano de los Siglos de Oro y algunas notas interlingüísticas

2017 ◽  
Vol 16 (16) ◽  
pp. 87
Author(s):  
Patricia Fernández Martín
Keyword(s):  
Golden Age ◽  
Theoretical Framework ◽  
Spanish Language ◽  
Romance Languages ◽  
Personal Pronouns ◽  
Dual Nature ◽  
Starting Point ◽  
Chronicles Of The Indies ◽  
History Of

El objetivo del presente trabajo es profundizar en la historia del funcionamiento de las construcciones castellanas {tener/llevar} + participio, tomando como centro de estudio la lengua de los siglos xvi y xvii y estableciendo ciertas comparaciones, a lo largo del texto, con otras lenguas romances, en especial el asturiano. El punto de partida se encuentra en la idea de que los problemas que crean estas construccionesse deben esencialmente a la doble naturaleza del participio (adjetival y verbal), solo comprensible inserta en un continuum entre el puro adjetivo y el puro verbo. Para ello, comenzaremos estableciendo, en el marco teórico, nuestro concepto de perífrasis verbal de participio y su aplicación a las construcciones que nos ocupan en el español de los Siglos de Oro. En una segunda parte, analizaremos el funcionamiento de dichas estructuras en el español clásico, empleando un corpus formado por tres génerosdiscursivos, escritos entre 1519 y 1656, que componen sendos subapartados (novelas picarescas, epístolas y crónicas de Indias). La principal conclusión es que los géneros discursivos no afectan a las construcciones de participio en la misma medida en que puede afectar a otros fenómenos gramaticales, como los pronombres personales.The aim of this work is to deepen in the history of the Spanish structures{tener/llevar} + participle, taking into account the language of the 16th and 17th centuries and offering certain comparisons with other Romance languages, specially Asturian. The starting point lies in the idea that the problems that create these constructions are essentially due to the dual nature of the participle (between a verb and an adjective), which can be only understood into a continuum, whose ends are the pure adjective and the pure verb. For that, we will start setting our concept of participial periphrases in the theoretical framework, as well as its applicationto the Spanish language spoken in the Golden Age. Then, we analyze how these structures work in that Spanish, using a corpus formed by three discourse genres (picaresque novels, letters and chronicles of the Indies), whose texts were written between 1519 and 1656. Finally, all of which allows to conclude that the discourse genres do not affect the appearance of the constructions of participle in the same extent that it may affect other grammatical phenomena, such as personal pronouns.

scholarly journals Simulation and Sensitivity Analysis and Cross-Validation, Demonstrating the Utility of Genteract GxE Discovery methods

2020 ◽  
Author(s):  
Brody Holohan ◽  
Raphael Laderman
Keyword(s):  
Complex Traits ◽  
Statistical Power ◽  
Cross Validation ◽  
Environmental Changes ◽  
Disease Incidence ◽  
Limiting Factor ◽  
Individual Response ◽  
Analytical Technique ◽  
Gene Environment ◽  
Study Results

AbstractGene-environment interactions are at the heart of why many complex traits are not fully heritable, and why prediction of disease incidence and individual response to environmental changes based on genetics has been underwhelming in utility. Understanding these interactions is the primary limiting factor for the application of personalized medicine, but current methods are not well suited for dealing with complex traits that pose both a dimensionality and sparse data problem to unsupervised analysis methods. Genteract has developed a proprietary analytical technique that allows for detection and interpretation of GxEs regarding specific pairs of a single phenotype with a single environmental factor; these methods allow us to develop a platform that can be used to predict how individuals will respond to changes in their environment based on their genetics. To validate the methods we performed two types of testing: cross-validation against a dataset of clinical study results, and application of the methods in a simulated dataset. These tests enable a greater understanding of the methods’ utility, statistical power and predictive capabilities.

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