Related Experiment Video
Updated: Aug 16, 2026
08:27
Large-Scale Multi-Omics Genome-Wide Association Studies (Mo-GWAS): Guidelines for Sample Preparation and Normalization
Published on: July 27, 2021
Longitudinal genome-wide analysis reveals putative non-additive loci in trait development
Ralph Porneso1, Alexandra Havdahl2, Espen Moen Eilertsen1
1PROMENTA Research Center, Department of Psychology, University of Oslo, Oslo, Norway.
Cell Reports
|August 14, 2026
Summary
Standard genetic models overlook non-additive effects. Our new model identifies 76 genetic loci linked to non-additive effects in growth and cognitive traits, revealing complex genetic contributions to development.
Area of Science:
- Genetics
- Developmental Biology
- Biostatistics
Background:
- Complex traits result from genotype, environment, and developmental interactions.
- Standard genetic models often assume additive effects, potentially missing non-additive genetic influences.
- Non-additive genetic effects play a crucial role in understanding trait variation.
Purpose of the Study:
- To introduce a novel longitudinal log-linear variance and genotype-by-time model.
- To detect associations between within-individual variation and putative non-additive genetic effects.
- To investigate non-additive genetic contributions to early growth and cognitive traits.
Main Methods:
- Developed a longitudinal log-linear variance and genotype-by-time model.
- Applied the model to large datasets (45,000-65,000 individuals) for infant growth and cognitive traits.
- Analyzed within-individual variation to identify departures from additivity.
Main Results:
- Identified 76 lead putative non-additive loci for growth and cognitive traits.
- These loci showed a 16-fold enrichment for cis-regulatory interactions.
- Observed a correlation between additive and putative non-additive effects ('effect pleiotropy'), suggesting non-additive effects are partly captured by standard models.
Conclusions:
- Non-additive genetic effects contribute significantly to trait development.
- Standard genome-wide association study (GWAS) parameterizations assuming additivity may obscure these non-additive effects.
- The developed model offers a new approach to uncover complex genetic architectures of traits.
Related Concept Videos
01:11Genome-wide Association Studies-GWAS
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
GWAS does not require the identification of the target gene involved in...
01:18Polygenic Traits
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
01:18Polygenic Traits
When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
01:49Multiple Allele Traits
The Concept of Multiple Allelism
01:49Multiple Allele Traits
The Concept of Multiple Allelism
01:19X-linked Traits
In most mammalian species, females have two X sex chromosomes and males have an X and Y. As a result, mutations on the X chromosome in females may be masked by the presence of a normal allele on the second X. In contrast, a mutation on the X chromosome in males more often causes observable biological defects, as there is no normal X to compensate. Trait variations arising from mutations on the X chromosome are called “X-linked”.