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Updated: Jan 3, 2026

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

Modelling multilocus selection in an individual-based, spatially-explicit landscape genetics framework.

Erin L Landguth¹, Brenna R Forester², Andrew J Eckert³

¹School of Public and Community Health Sciences, University of Montana, Missoula, MT, USA.

Molecular Ecology Resources

|November 27, 2019

Summary

This summary is machine-generated.

We developed a new module for landscape genetics software to simulate multilocus selection driven by environmental gradients. This tool enhances the study of gene flow and selection interactions in complex landscapes.

Keywords:

CDMetaPOP CDPOP computer simulation fitness surfaces landscape resistance natural selection

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Area of Science:

Ecology
Evolutionary Biology
Genetics

Background:

Landscape genetics studies the interplay between ecological processes and genetic variation.
Understanding how environmental gradients influence selection across multiple genes is crucial.
Existing models often lack the flexibility to simulate complex, multivariate selection pressures.

Purpose of the Study:

To introduce a new module for CDPOP and CDMetaPOP enabling simulation of multilocus selection.
To provide a flexible platform for evaluating genotype-environment associations under multivariate selection.
To investigate the combined effects of gene flow and selection in spatially explicit landscapes.

Main Methods:

Implemented a new module using a linear additive model for multilocus selection simulation.
Utilized a spatially-explicit, individual-based framework.
Validated the module with Wright-Fisher simulations and evaluated complex landscape scenarios.

Main Results:

The module successfully simulates multilocus selection influenced by multiple environmental variables.
Demonstrated simulations across simple and complex selection landscapes with linked loci.
Showcased the ability to model varying selection strengths and gene flow levels.

Conclusions:

The new module offers a valuable tool for landscape genetics research.
Enables explicit evaluation of gene flow and selection interactions under diverse environmental conditions.
Facilitates a deeper understanding of evolutionary processes in complex landscapes.