scholarly journals Genetic Architecture of Growth Traits Revealed by Global Epistatic Interactions

2011 ◽  
Vol 3 ◽  
pp. 909-914 ◽  
Author(s):  
Lin Xu ◽  
Huifeng Jiang ◽  
Hong Chen ◽  
Zhenglong Gu
Keyword(s):  
Genetic Architecture ◽  
Growth Traits ◽  
Epistatic Interactions

scholarly journals An Overview of Genomic Approaches for Characterizing the Genetic Architecture of Growth Traits in Chickens

2020 ◽  
Vol 65 (1) ◽  
pp. 65-78
Author(s):  
Prabuddha MANJULA ◽  
Sunghyun CHO ◽  
Dongwon SEO ◽  
Nobuhiko YAMAUCHI ◽  
Jun Heon LEE
Keyword(s):  
Genetic Architecture ◽  
Growth Traits

scholarly journals Big fish, little fish: a multi-omics investigation of growth traits in silver trevally (Pseudocaranx georgianus – araara)

2021 ◽  
Author(s):  
◽  
Noémie Valenza-Troubat
Keyword(s):  
New Zealand ◽  
Linkage Mapping ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
Growth Traits ◽  
Expression Patterns ◽  
Linkage Groups ◽  
Phenotypic Data ◽  
Genome Wide ◽  
A Genome

<p><b>Understanding the relationship between DNA sequence variation and the diversity of observable traits across the tree of life is a central research theme in biology. In all organisms, most traits vary continuously between individuals. Explaining the genetic basis of this quantitative variation requires disentangling genetic from non-genetic factors, as well as their interactions. The identification of causal genetic variants yields fundamental insights into how evolution creates diversity across the tree of life. Ultimately, this information can be used for medical, environmental and agricultural applications. Aquaculture is an industry that is experiencing significant global growth and is benefiting from the advances of genomic research. Genomic information helps to improve complex commercial phenotypes such as growth traits, which are easily quantified visually, but influenced by polygenes and multiple environmental factors, such as temperature. In the context of a global food crisis and environmental change, there is an urgent need not only to understand which genetic variants are potential candidates for selection gains, but also how the architecture of these traits are composed (e.g. monogenes, polygenes) and how they are influenced by and interact with the environment. The overall goal of this thesis research was to generate a genome-wide multi-omics dataset matched with exhaustive phenotypic information derived from a F0-F1 pedigree to investigate the quantitative genetic basis of growth in the New Zealand silver trevally (Pseudocaranx georgianus). These data were used to identify genomic regions that co-segregate with growth traits, and to describe the regulation of the genes involved in response to temperature fluctuations. The findings of this research helped gain fundamental insights into the genotype–phenotype map in an important teleost species and understand its ability to dynamically respond to temperature variations. This will ultimately support the establishment of a genomics-informed New Zealand aquaculture breeding programme. </b></p> <p>Chapter 1 of this thesis provides an overview of how genes interact with the environment to produce various growth phenotypes and how an understanding of this is important in aquaculture. This first chapter provides the deeper context for the research in subsequent data chapters. </p> <p>Chapter 2 describes the study population, the collection of phenotypic and genotypic data, and a first description of the genetic parameters of growth traits in trevally. A combination of Whole Genome Sequencing (WGS) and Genotyping-By-Sequencing (GBS) techniques were used to generate 60 thousand Single Nucleotide Polymorphism (SNP) markers for individuals in a two-generation pedigree. Together with phenotypic data, the genotyping data were used to reconstruct the pedigree, measure inbreeding levels, and estimate heritability for 10 growth traits. Parents were identified for 63% of the offspring and successful pedigree reconstruction indicated highly uneven contributions of each parent, and between the sexes, to the subsequent generation. The average inbreeding levels did not change between generations, but were significantly different between families. Growth patterns were found to be similar to that of other carangids and subject to seasonal variations. Heritability as well as genetic and phenotypic correlations were estimated using both a pedigree and a genomic relatedness matrix. All growth trait heritability estimates and correlations were found to be consistently high and positively correlated to each other. </p> <p>In Chapter 3, genotypic and phenotypic data were used to carry out linkage mapping and a genome-wide association study (GWAS) to map quantitative trait loci (QTLs) associated with growth differences in the F1 population. A linkage map was generated using the largest family, which allowed to scan for rare variants associated with the traits. The linkage map reported in this thesis is the first one for the Pseudocaranx genus and one of the densest for the carangid family. It included 19,861 SNPs contained in 24 linkage groups, which correspond to the 24 trevally chromosomes. Eight significant QTLs associated with height, length and weight were discovered on three linkage groups. Using GWAS, 113 SNPs associated with nine traits were identified and 29 genetic growth hot spots were uncovered. Two of the GWAS markers co-located with the QTLs discovered with the linkage mapping analysis. This demonstrates that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex phenotypes, such as growth, and provides important insights into the genetic architecture of these traits. </p> <p>Chapter 4, the last data chapter, investigates plasticity in gene expression patterns and growth of juvenile trevally, in response to different temperatures. Temperature conditions were experimentally manipulated for 1 month to mimic seasonal extremes. Phenotypic differences in growth were measured in 400 individuals, and the gene expression patterns of the pituitary gland and the liver were compared across treatments in a subset of 100 individuals, using RNA sequencing. Results showed that growth increased 50% more in the warmer compared with the colder condition, suggesting that temperature has a large impact on the metabolic activity associated with growth. We were able to annotate 27,887 gene models and found 39 differentially expressed genes (DEGs) in the pituitary, and 238 in the liver. Of these, 6 DEGs showed a common expression pattern between the tissues. Annotated blast matches of all DEGs revealed genes linked to major pathways affecting metabolism and reproduction. Our results indicate that native New Zealand trevally exhibit predictable plastic regulatory responses to temperature stress and the genes identified provide excellent for selective breeding objectives and studied how populations may adapt to increasing temperatures.</p> <p>Finally, Chapter 5 discusses the implications, future directions, and application of this research for trevally and other breeding programmes. It more broadly highlights the insights that were gained on the genetic architecture of growth, and the role of temperature in interacting and modulating genes involved in plastic growth responses.</p>

The potential for rapid speciation in plants

Genome ◽  
1989 ◽  
Vol 31 (1) ◽  
pp. 203-210 ◽  
Author(s):  
Mark R. Macnair
Keyword(s):  
Reproductive Isolation ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
Natural Populations ◽  
Direct Result ◽  
Epistatic Interactions ◽  
Genetic Changes ◽  
Rapid Speciation ◽  
Genetic Revolution ◽  
Self Fertilization

Speciation involves both ecological adaptation and reproductive isolation. This paper reviews various ways in which plants could achieve reproductive isolation as a direct result of adaptation to prevailing conditions, particularly through changes in flowering time, the adoption of self-fertilization, and changes in flower morphology so that different pollinators are attracted. These characters are likely to have a relatively simple genetic architecture, and there must frequently be genetic variance for them in natural populations. It is argued that speciation could thus be initiated swiftly in plants, without any need for a "genetic revolution" or the fixation of genes with strongly epistatic interactions. Postmating barriers also often have a simple genetic basis in plants, and so could also evolve swiftly if associated with an adaptive response. The nature of the genetic changes associated with speciation in a number of recent speciation events in Layia, Stephanomeria, and Mimulus is reviewed.Key words: Speciation, adaptation, reproductive isolation.

scholarly journals The genetic architecture of growth traits in Salix matsudana under salt stress

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Jian Zhang ◽  
Huwei Yuan ◽  
Qingshan Yang ◽  
Min Li ◽  
Ying Wang ◽  
...  
Keyword(s):  
Salt Stress ◽  
Genetic Architecture ◽  
Growth Traits ◽  
Salix Matsudana

scholarly journals Epistasis detection and modeling for genomic selection in cowpea (Vigna unguiculata. L. Walp.)

2019 ◽  
Author(s):  
Marcus O. Olatoye ◽  
Zhenbin Hu ◽  
Peter O. Aikpokpodion
Keyword(s):  
Genomic Selection ◽  
Flowering Time ◽  
Marker Assisted Selection ◽  
Fixed Effects ◽  
Genetic Architecture ◽  
Phytochrome A ◽  
Epistatic Interactions ◽  
Moderate Effect ◽  
Advanced Generation ◽  
Non Parametric

AbstractGenetic architecture reflects the pattern of effects and interaction of genes underling phenotypic variation. Most mapping and breeding approaches generally consider the additive part of variation but offer limited knowledge on the benefits of epistasis which explains in part the variation observed in traits. In this study, the cowpea multiparent advanced generation inter-cross (MAGIC) population was used to characterize the epistatic genetic architecture of flowering time, maturity, and seed size. In addition, considerations for epistatic genetic architecture in genomic-enabled breeding (GEB) was investigated using parametric, semi-parametric, and non-parametric genomic selection (GS) models. Our results showed that large and moderate effect sized two-way epistatic interactions underlie the traits examined. Flowering time QTL colocalized with cowpea putative orthologs of Arabidopsis thaliana and Glycine max genes like PHYTOCLOCK1 (PCL1 [Vigun11g157600]) and PHYTOCHROME A (PHY A [Vigun01g205500]). Flowering time adaptation to long and short photoperiod was found to be controlled by distinct and common main and epistatic loci. Parametric and semi-parametric GS models outperformed non-parametric GS model. Using known QTL as fixed effects in GS models improved prediction accuracy when traits were controlled by both large and moderate effect QTL. In general, our study demonstrated that prior understanding the genetic architecture of a trait can help make informed decisions in GEB. This is the first report to characterize epistasis and provide insights into the underpinnings of GS versus marker assisted selection in cowpea.

scholarly journals Heritability Coverage of Standard Biometric Models under various Phenotypic Architectures

2019 ◽  
Author(s):  
Michael Maraun ◽  
Moritz Heene ◽  
Philipp Sckopke
Keyword(s):  
Genetic Architecture ◽  
Covariance Matrices ◽  
Simulation Studies ◽  
Epistatic Interactions ◽  
Parameter Recovery ◽  
Genetic Environment ◽  
Recovery Performance ◽  
H2 Recovery ◽  
The Impact ◽  
Biometric Model

The behavioural scientist who requires an estimate of narrow heritability, h2, will conduct a twin study, and input the resulting estimated covariance matrices into a particular mode of estimation, the latter derived under supposition of the standard biometric model (SBM). It is now widely acknowledged that the standard biometric model can be expected to misrepresent, in manifold ways, the phenotypic (genetic) architecture of human traits. The impact of this misrepresentation on the accuracy of h2 estimation is unknown. Herein, we aimed to shed some light on this general issue, by undertaking three simulation studies. In each, the parameter recovery performance of five modes- Falconer's coefficient and the SEM models, ACDE, ADE, ACE, and AE- was investigated when they encountered a constructed, non-SBM, architecture, under a particular informational input. In study 1, the architecture was single-locus with dominance effects and genetic-environment covariance, and the input was { ΣMZ,T, ΣDZ,T, ΣMZ,A, ΣDZ,A}; in study 2, the architecture was identical to that of study 1, but the informational input was { ΣMZ,T, ΣDZ,T}; and in study 3, the architecture was multi-locus with dominance effects, genetic-environment covariance, and epistatic interactions. The informational input was {ΣMZ,T, ΣDZ,T, ΣMZ,A, ΣDZ,A}. The results suggest that conclusions regarding the coverage of h2 must be drawn conditional on a) the general class of generating architecture in play; b) specifics of the architecture’s parametric instantiations; c) the informational input into a mode of estimation; and d) the particular mode of estimation employed. In general, the results showed that more complicated the generating architecture, the poorer a mode’s h2 recovery performance. Random forest analyses furthermore revealed that, depending on the genetic architecture, h2, the dominance and locus additive parameter, and proportions of alleles were involved in complex interaction effects impacting on h2 parameter recovery performance of a mode of estimation. Data and materials: https://osf.io/aq9sx/

scholarly journals Big fish, little fish: a multi-omics investigation of growth traits in silver trevally (Pseudocaranx georgianus – araara)

2021 ◽  
Author(s):  
◽  
Noémie Valenza-Troubat
Keyword(s):  
New Zealand ◽  
Linkage Mapping ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
Growth Traits ◽  
Expression Patterns ◽  
Linkage Groups ◽  
Phenotypic Data ◽  
Genome Wide ◽  
A Genome

<p><b>Understanding the relationship between DNA sequence variation and the diversity of observable traits across the tree of life is a central research theme in biology. In all organisms, most traits vary continuously between individuals. Explaining the genetic basis of this quantitative variation requires disentangling genetic from non-genetic factors, as well as their interactions. The identification of causal genetic variants yields fundamental insights into how evolution creates diversity across the tree of life. Ultimately, this information can be used for medical, environmental and agricultural applications. Aquaculture is an industry that is experiencing significant global growth and is benefiting from the advances of genomic research. Genomic information helps to improve complex commercial phenotypes such as growth traits, which are easily quantified visually, but influenced by polygenes and multiple environmental factors, such as temperature. In the context of a global food crisis and environmental change, there is an urgent need not only to understand which genetic variants are potential candidates for selection gains, but also how the architecture of these traits are composed (e.g. monogenes, polygenes) and how they are influenced by and interact with the environment. The overall goal of this thesis research was to generate a genome-wide multi-omics dataset matched with exhaustive phenotypic information derived from a F0-F1 pedigree to investigate the quantitative genetic basis of growth in the New Zealand silver trevally (Pseudocaranx georgianus). These data were used to identify genomic regions that co-segregate with growth traits, and to describe the regulation of the genes involved in response to temperature fluctuations. The findings of this research helped gain fundamental insights into the genotype–phenotype map in an important teleost species and understand its ability to dynamically respond to temperature variations. This will ultimately support the establishment of a genomics-informed New Zealand aquaculture breeding programme. </b></p> <p>Chapter 1 of this thesis provides an overview of how genes interact with the environment to produce various growth phenotypes and how an understanding of this is important in aquaculture. This first chapter provides the deeper context for the research in subsequent data chapters. </p> <p>Chapter 2 describes the study population, the collection of phenotypic and genotypic data, and a first description of the genetic parameters of growth traits in trevally. A combination of Whole Genome Sequencing (WGS) and Genotyping-By-Sequencing (GBS) techniques were used to generate 60 thousand Single Nucleotide Polymorphism (SNP) markers for individuals in a two-generation pedigree. Together with phenotypic data, the genotyping data were used to reconstruct the pedigree, measure inbreeding levels, and estimate heritability for 10 growth traits. Parents were identified for 63% of the offspring and successful pedigree reconstruction indicated highly uneven contributions of each parent, and between the sexes, to the subsequent generation. The average inbreeding levels did not change between generations, but were significantly different between families. Growth patterns were found to be similar to that of other carangids and subject to seasonal variations. Heritability as well as genetic and phenotypic correlations were estimated using both a pedigree and a genomic relatedness matrix. All growth trait heritability estimates and correlations were found to be consistently high and positively correlated to each other. </p> <p>In Chapter 3, genotypic and phenotypic data were used to carry out linkage mapping and a genome-wide association study (GWAS) to map quantitative trait loci (QTLs) associated with growth differences in the F1 population. A linkage map was generated using the largest family, which allowed to scan for rare variants associated with the traits. The linkage map reported in this thesis is the first one for the Pseudocaranx genus and one of the densest for the carangid family. It included 19,861 SNPs contained in 24 linkage groups, which correspond to the 24 trevally chromosomes. Eight significant QTLs associated with height, length and weight were discovered on three linkage groups. Using GWAS, 113 SNPs associated with nine traits were identified and 29 genetic growth hot spots were uncovered. Two of the GWAS markers co-located with the QTLs discovered with the linkage mapping analysis. This demonstrates that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex phenotypes, such as growth, and provides important insights into the genetic architecture of these traits. </p> <p>Chapter 4, the last data chapter, investigates plasticity in gene expression patterns and growth of juvenile trevally, in response to different temperatures. Temperature conditions were experimentally manipulated for 1 month to mimic seasonal extremes. Phenotypic differences in growth were measured in 400 individuals, and the gene expression patterns of the pituitary gland and the liver were compared across treatments in a subset of 100 individuals, using RNA sequencing. Results showed that growth increased 50% more in the warmer compared with the colder condition, suggesting that temperature has a large impact on the metabolic activity associated with growth. We were able to annotate 27,887 gene models and found 39 differentially expressed genes (DEGs) in the pituitary, and 238 in the liver. Of these, 6 DEGs showed a common expression pattern between the tissues. Annotated blast matches of all DEGs revealed genes linked to major pathways affecting metabolism and reproduction. Our results indicate that native New Zealand trevally exhibit predictable plastic regulatory responses to temperature stress and the genes identified provide excellent for selective breeding objectives and studied how populations may adapt to increasing temperatures.</p> <p>Finally, Chapter 5 discusses the implications, future directions, and application of this research for trevally and other breeding programmes. It more broadly highlights the insights that were gained on the genetic architecture of growth, and the role of temperature in interacting and modulating genes involved in plastic growth responses.</p>

scholarly journals Residual Heterozygosity and Epistatic Interactions Underlie the Complex Genetic Architecture of Yield in Diploid Potato

Genetics ◽  
2019 ◽  
Vol 212 (1) ◽  
pp. 317-332 ◽  
Author(s):  
Alexandre P. Marand ◽  
Shelley H. Jansky ◽  
Joseph L. Gage ◽  
Andy J. Hamernik ◽  
Natalia de Leon ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Diploid Potato ◽  
Epistatic Interactions ◽  
Residual Heterozygosity

scholarly journals Genetic architecture of growth traits in Populus revealed by integrated quantitative trait locus ( QTL ) analysis and association studies

2015 ◽  
Vol 209 (3) ◽  
pp. 1067-1082 ◽  
Author(s):  
Qingzhang Du ◽  
Chenrui Gong ◽  
Qingshi Wang ◽  
Daling Zhou ◽  
Haijiao Yang ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Qtl Analysis ◽  
Quantitative Trait ◽  
Genetic Architecture ◽  
Growth Traits ◽  
Association Studies ◽  
Trait Locus

Sex differences and non-additivity in the effects of genes on personality

Twin Research ◽  
1998 ◽  
Vol 1 (3) ◽  
pp. 131-137 ◽  
Author(s):  
Lindon J Eaves ◽  
Andrew C Heath ◽  
Michael C Neale ◽  
John K Hewitt ◽  
Nicholas G Martin
Keyword(s):  
Sex Differences ◽  
Genetic Architecture ◽  
Large Data ◽  
Family Resemblance ◽  
Genetic Effects ◽  
Shared Environment ◽  
Integrated Analysis ◽  
Epistatic Interactions ◽  
Large Samples ◽  
Additive Genetic Effects

AbstractNew large-sample data show that non-additive genetic effects, probably epistatic interactions between loci, and sex-limited gene expression are significant features of the genetic architecture of human personality as measured by questionnaire scales of extraversion and neuroticism. Three large data sets – new data on large samples (n = 20 554) of US twins, their spouses, parents, siblings and children, correlations for Australian twins (n = 7 532), and previously published twin data from Finland (n = 14 288) – are subjected to an integrated analysis to test alternative hypotheses about the genetic causes of family resemblance in personality. When allowance is made for differences in reliability of the scales, the combined data are consistent with the same model for variation. There are significant amounts of genetic non-additivity for both dimensions of personality. The evidence favours additive × additive epistatic interactions rather than dominance. In the case of neuroticism, there is especially strong evidence of sex differences in genetic architecture favouring a greater relative contribution of non-additive genetic effects in males. The data confirm previous claims to find no major contribution of the shared environment of twins and siblings to these dimensions of personality. Correlations between spouses are zero, and the correlations for very large samples of siblings and non-identical twins do not differ significantly.

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