Related Experiment Video
Updated: May 8, 2026
13:55
Combined Immunofluorescence and DNA FISH on 3D-preserved Interphase Nuclei to Study Changes in 3D Nuclear Organization
Published on: February 3, 2013
A method for estimating the effective number of loci affecting a quantitative character
1Department of Integrative Biology, University of California, Berkeley, CA 94720-3140, USA.
Theoretical Population Biology
|August 27, 2013
Summary
A new statistical method estimates the number and additive effects of genetic loci influencing quantitative traits. This approach requires family data and performs well with thousands of families, aiding genetic variance analysis.
Area of Science:
- Quantitative genetics
- Statistical genetics
- Population genetics
Background:
- Understanding the genetic architecture of quantitative traits is crucial in biology and medicine.
- Estimating the number and effects of underlying genetic loci is a complex challenge.
- Existing methods often require extensive genetic marker data or specific population structures.
Purpose of the Study:
- To introduce a novel likelihood-based method for jointly estimating the number of loci and their additive effects on quantitative traits.
- To provide a statistical framework applicable to randomly mating populations with available family data.
- To adapt the method for incorporating previously identified genetic associations.
Main Methods:
- Developed a likelihood method utilizing parental and offspring phenotypes.
- Leveraged the relationship between offspring variance, parental phenotypes, and the number of loci.
- Employed simulations to assess method performance and parametric bootstrap for confidence intervals.
Main Results:
- The method performs well with sufficient family data (thousands of families).
- Simulations indicate robustness under Hardy-Weinberg and linkage equilibrium assumptions.
- Applied to crown-rump length in African green monkeys, it estimated 112 loci with an additive effect of 0.26 cm, with a lower confidence bound of 14 loci.
Conclusions:
- The introduced likelihood method offers a powerful tool for dissecting the genetic basis of quantitative traits.
- It provides estimates for the number of loci and their additive effects, even when loci are unknown.
- The method is applicable to various species and traits, enhancing genetic variance analysis.
Related Concept Videos
01:49Hardy-Weinberg Principle
Diploid organisms have two alleles of each gene, one from each parent, in their somatic cells. Therefore, each individual contributes two alleles to the gene pool of the population. The gene pool of a population is the sum of every allele of all genes within that population and has some degree of variation. Genetic variation is typically expressed as a relative frequency, which is the percentage of the total population that has a given allele, genotype or phenotype.
01:24One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
On...
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
01:05Properties of the Root Locus
The root locus method is an invaluable tool for analyzing higher-order systems without needing to factor the denominator of the transfer function. A pole of the system is identified when the characteristic polynomial in the transfer function's denominator equals zero.
To determine if a point lies on the root locus, the criterion involves the sum of angles contributed by all poles and zeros to that point. Specifically, this sum must be an odd multiple of 180 degrees. The gain at any point on the...
To determine if a point lies on the root locus, the criterion involves the sum of angles contributed by all poles and zeros to that point. Specifically, this sum must be an odd multiple of 180 degrees. The gain at any point on the...
01:49Multiple Allele Traits
The Concept of Multiple Allelism
01:09Epistasis Analysis
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...