scholarly journals From Galton to GWAS: quantitative genetics of human height

2010 ◽  
Vol 92 (5-6) ◽  
pp. 371-379 ◽  
Author(s):  
PETER M. VISSCHER ◽  
BRIAN McEVOY ◽  
JIAN YANG
Keyword(s):  
Genetic Variation ◽  
Quantitative Genetics ◽  
Genetic Architecture ◽  
Human Genetics ◽  
Effect Sizes ◽  
Phenotypic Differences ◽  
Large Samples ◽  
Marker Data ◽  
Genomic Technologies ◽  
Underlying Causes

SummaryHeight has been studied in human genetics since the late 1800s. We review what we have learned about the genetic architecture of this trait from the resemblance between relatives and from genetic marker data. All empirical evidence points towards height being highly polygenic, with many loci contributing to variation in the population and most effect sizes appear to be small. Nevertheless, combining new genetic and genomic technologies with phenotypic measures on height on large samples facilitates new answers to old questions, including the basis of assortative mating in humans, estimation of non-additive genetic variation and partitioning between-cohort phenotypic differences into genetic and non-genetic underlying causes.

scholarly journals A scalable method for estimating the regional polygenicity of complex traits

2020 ◽  
Author(s):  
Ruth Johnson ◽  
Kathryn S. Burch ◽  
Kangcheng Hou ◽  
Mario Paciuc ◽  
Bogdan Pasaniuc ◽  
...  
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Human Genetics ◽  
Effect Sizes ◽  
Marginal Effect ◽  
High Cholesterol ◽  
Genome Wide ◽  
Unbiased Estimates ◽  
Genomic Regions ◽  
Insight Into

AbstractA key question in human genetics is understanding the proportion of SNPs modulating a particular phenotype or the proportion of susceptibility SNPs for a disease, termed polygenicity. Previous studies have observed that complex traits tend to be highly polygenic, opposing the previous belief that only a handful of SNPs contribute to a trait. Beyond these genome-wide estimates, the distribution of polygenicity across genomic regions as well as the genomic factors that affect regional polygenicity remain poorly understood. A reason for this gap is that methods for estimating polygenicity utilize SNP effect sizes from GWAS. However, estimating regional polygenicity from GWAS effect sizes involves untangling the correlation between SNPs due to LD, leading to intractable computations for even a small number of SNPs. In this work, we propose a scalable method, BEAVR, to estimate the regional polygenicity of a trait given marginal effect sizes from GWAS and LD information. We implement a Gibbs sampler to estimate the posterior distribution of the regional polygenicity and derive a fast, algorithmic update to circumvent the computational bottlenecks associated with LD. The runtime of our algorithm is 𝒪(MK) for M SNPs and K susceptibility SNPs, where the number of susceptibility SNPs is typically K ≪ M. By modeling the full LD structure, we show that BEAVR provides unbiased estimates of polygenicity compared to previous methods that only partially model LD. Finally, we show how estimates of regional polygenicity for BMI, eczema, and high cholesterol provide insight into the regional genetic architecture of each trait.

Maintenance of Quantitative Genetic Variation

2018 ◽  
Author(s):  
Bruce Walsh ◽  
Michael Lynch
Keyword(s):  
Genetic Variation ◽  
Quantitative Genetics ◽  
Stabilizing Selection ◽  
Quantitative Genetic ◽  
Wide Range

One of the major unresolved issues in quantitative genetics is what accounts for the amount of standing genetic variation in traits. A wide range of models, all reviewed in this chapter, have been proposed, but none fit the data, either giving too much variation or too little apparent stabilizing selection.

scholarly journals Genetic variation in the Middle East—an opportunity to advance the human genetics field

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Ahmad N. Abou Tayoun ◽  
Heidi L. Rehm
Keyword(s):  
Genetic Variation ◽  
Middle East ◽  
Human Genetics ◽  
High Impact ◽  
Limiting Factors ◽  
Sequencing Data ◽  
Clinical Sequencing ◽  
The World ◽  
Genomic Studies

AbstractWe highlight the current lack of representation of the Middle East from large genomic studies and emphasize the expected high impact of cataloging its variation. We discuss the limiting factors and possible solutions to generating and accessing research and clinical sequencing data from this part of the world.

scholarly journals Focused Strategies for Defining the Genetic Architecture of Congenital Heart Defects

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 827
Author(s):  
Lisa J. Martin ◽  
D Woodrow Benson
Keyword(s):  
Genetic Variation ◽  
Congenital Heart Defects ◽  
Heart Development ◽  
Genetic Architecture ◽  
Congenital Heart ◽  
Rare Variants ◽  
Heart Defects ◽  
Genetic Origin ◽  
Genetic Studies ◽  
The Ideal

Congenital heart defects (CHD) are malformations present at birth that occur during heart development. Increasing evidence supports a genetic origin of CHD, but in the process important challenges have been identified. This review begins with information about CHD and the importance of detailed phenotyping of study subjects. To facilitate appropriate genetic study design, we review DNA structure, genetic variation in the human genome and tools to identify the genetic variation of interest. Analytic approaches powered for both common and rare variants are assessed. While the ideal outcome of genetic studies is to identify variants that have a causal role, a more realistic goal for genetic analytics is to identify variants in specific genes that influence the occurrence of a phenotype and which provide keys to open biologic doors that inform how the genetic variants modulate heart development. It has never been truer that good genetic studies start with good planning. Continued progress in unraveling the genetic underpinnings of CHD will require multidisciplinary collaboration between geneticists, quantitative scientists, clinicians, and developmental biologists.

scholarly journals Sex, amitosis, and evolvability in the ciliate Tetrahymena thermophila

2021 ◽  
Author(s):  
Jason A Tarkington ◽  
Hao Zhang ◽  
Ricardo Azevedo ◽  
Rebecca Zufall
Keyword(s):  
Genetic Variation ◽  
Experimental Evolution ◽  
Evolutionary Biology ◽  
Genetic Architecture ◽  
Nuclear Division ◽  
Tetrahymena Thermophila ◽  
Laboratory Populations ◽  
Evolutionary Success ◽  
Sexual Progeny ◽  
Open Question

Understanding the mechanisms that generate genetic variation, and thus contribute to the process of adaptation, is a major goal of evolutionary biology. Mutation and genetic exchange have been well studied as mechanisms to generate genetic variation. However, there are additional processes that may also generate substantial genetic variation in some populations and the extent to which these variation generating mechanisms are themselves shaped by natural selection is still an open question. Tetrahymena thermophila is a ciliate with an unusual mechanism of nuclear division, called amitosis, which can generate genetic variation among the asexual descendants of a newly produced sexual progeny. We hypothesize that amitosis thus increases the evolvability of newly produced sexual progeny relative to species that undergo mitosis. To test this hypothesis, we used experimental evolution and simulations to compare the rate of adaptation in T. thermophila populations founded by a single sexual progeny to parental populations that had not had sex in many generations. The populations founded by a sexual progeny adapted more quickly than parental populations in both laboratory populations and simulated populations. This suggests that the additional genetic variation generated by amitosis of a heterozygote can increase the rate of adaptation following sex and may help explain the evolutionary success of the unusual genetic architecture of Tetrahymena and ciliates more generally.

scholarly journals A method for identifying genetic heterogeneity within phenotypically-defined disease subgroups

2016 ◽  
Author(s):  
James Liley ◽  
John A Todd ◽  
Chris Wallace
Keyword(s):  
Genetic Variants ◽  
Genetic Architecture ◽  
Effect Sizes ◽  
Thyroid Peroxidase ◽  
Global Test ◽  
Genome Wide ◽  
Thyroid Peroxidase Antibody ◽  
Antibody Positivity ◽  
Post Hoc

AbstractMany common diseases show wide phenotypic variation. We present a statistical method for determining whether phenotypically defined subgroups of disease cases represent different genetic architectures, in which disease-associated variants have different effect sizes in the two subgroups. Our method models the genome-wide distributions of genetic association statistics with mixture Gaussians. We apply a global test without requiring explicit identification of disease-associated variants, thus maximising power in comparison to a standard variant by variant subgroup analysis. Where evidence for genetic subgrouping is found, we present methods for post-hoc identification of the contributing genetic variants.We demonstrate the method on a range of simulated and test datasets where expected results are already known. We investigate subgroups of type 1 diabetes (T1D) cases defined by autoantibody positivity, establishing evidence for differential genetic architecture with thyroid peroxidase antibody positivity, driven generally by variants in known T1D associated regions.

scholarly journals Geographic patterns of human allele frequency variation: a variant-centric perspective

2020 ◽  
Author(s):  
Arjun Biddanda ◽  
Daniel P. Rice ◽  
John Novembre
Keyword(s):  
Genetic Variation ◽  
Gene Flow ◽  
Genetic Structure ◽  
Allele Frequency ◽  
Human Genetics ◽  
Geographic Region ◽  
Frequency Variation ◽  
Human Genetic Variation ◽  
Alternative Representation ◽  
Geographic Patterns

AbstractA key challenge in human genetics is to describe and understand the distribution of human genetic variation. Often genetic variation is described by showing relationships among populations or individuals, in each case drawing inferences over a large number of variants. Here, we present an alternative representation of human genetic variation that reveals the relative abundance of different allele frequency patterns across populations. This approach allows viewers to easily see several features of human genetic structure: (1) most variants are rare and geographically localized, (2) variants that are common in a single geographic region are more likely to be shared across the globe than to be private to that region, and (3) where two individuals differ, it is most often due to variants that are common globally, regardless of whether the individuals are from the same region or different regions. To guide interpretation of the results, we also apply the visualization to contrasting theoretical scenarios with varying levels of divergence and gene flow. Our variant-centric visualization clarifies the major geographic patterns of human variation and can be used to help correct potential misconceptions about the extent and nature of genetic differentiation among populations.

Hybrid Neural Genetic Architecture

2013 ◽  
pp. 245-270
Author(s):  
Emmanuel Buabin
Keyword(s):  
Genetic Algorithm ◽  
Human Nature ◽  
Recommender Systems ◽  
Genetic Architecture ◽  
Network Performance ◽  
Human Genetics ◽  
Systems Design ◽  
Splice Junction ◽  
Fully Integrated ◽  
Active Research

The objective is a neural-based feature selection in intelligent recommender systems. In particular, a hybrid neural genetic architecture is modeled based on human nature, interactions, and behaviour. The main contribution of this chapter is the development of a novel genetic algorithm based on human nature, interactions, and behaviour. The novel genetic algorithm termed “Buabin Algorithm” is fully integrated with a hybrid neural classifier to form a Hybrid Neural Genetic Architecture. The research presents GA in a more attractive manner and opens up the various departments of a GA for active research. Although no scientific experiment is conducted to compare network performance with standard approaches, engaged techniques reveal drastic reductions in genetic operator operations. For illustration purposes, the UCI Molecular Biology (Splice Junction) dataset is used. Overall, “Buabin Algorithm” seeks to integrate human related interactions into genetic algorithms as imitate human genetics in recommender systems design and understand underlying datasets explicitly.

scholarly journals Deconstruction of Vulnerability to Complex Diseases: Enhanced Effect Sizes and Power of Intermediate Phenotypes

2007 ◽  
Vol 7 ◽  
pp. 124-130 ◽  
Author(s):  
David Goldman ◽  
Francesca Ducci
Keyword(s):  
Effect Size ◽  
Complex Disease ◽  
Complex Diseases ◽  
Effect Sizes ◽  
Complex Disorders ◽  
Large Samples ◽  
Intermediate Phenotypes ◽  
Genome Association ◽  
Whole Genome Association ◽  
Disease Loci

The deconstruction of vulnerability to complex disease with the help of intermediate phenotypes, including the heritable and disease-associated endophenotypes, is a legacy of Henri Begleiter. Systematic searches for genes influencing complex disorders, including bipolar disorder, have recently been completed using whole genome association (WGA), identifying a series of validated loci. Using this information, it is possible to compare effect sizes of disease loci discovered in very large samples to the effect sizes of replicated functional loci determining intermediate phenotypes that are of essential interest in psychiatric disorders. It is shown that the genes influencing intermediate phenotypes tend to have a larger effect size. Furthermore, the WGA results reveal that the number of loci of large effect size for complex diseases is limited, and yet multiple functional loci have already been identified for intermediate phenotypes relevant to psychiatric diseases, and without the benefit of WGA.

Sign in / Sign up

Export Citation Format

Share Document