Stabilizing selection

Stabilizing selection (not to be confused with negative or purifying selection) is a type of natural selection in which the population mean stabilizes on a particular non-extreme trait value. This is thought to be the most common mechanism of action for natural selection because most traits do not appear to change drastically over time. Stabilizing selection commonly uses negative selection (a.k.a. purifying selection) to select against extreme values of the character. Stabilizing selection is the opposite of disruptive selection. Instead of favoring individuals with extreme phenotypes, it favors the intermediate variants. Stabilizing selection tends to remove the more severe phenotypes, resulting in the reproductive success of the norm or average phenotypes. This means that most common phenotype in the population is selected for and continues to dominate in future generations. The Russian evolutionary biologist Ivan Schmalhausen founded the theory of stabilizing selection, publishing a paper in Russian titled "Stabilizing selection and its place among factors of evolution" in 1941 and a monograph "Factors of Evolution: The Theory of Stabilizing Selection" in 1945. Stabilizing selection causes the narrowing of the phenotypes seen in a population. This is because the extreme phenotypes are selected against, causing reduced survival in organisms with those traits. This results in a population consisting of fewer phenotypes, with most traits representing the mean value of the population. This narrowing of phenotypes causes a reduction in genetic diversity in a population. Maintaining genetic variation is essential for the survival of a population because it is what allows them to evolve over time. In order for a population to adapt to changing environmental conditions they must have enough genetic diversity to select for new traits as they become favorable. There are four primary types of data used to quantify stabilizing selection in a population. The first type of data is an estimation of fitness of different phenotypes within a single generation.

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related concepts (7)

Related courses (47)

Related lectures (308)

Related MOOCs (8)

AR-219: Advanced CAO and Integrated Modeling DIM

1ère année: bases nécessaires à la représentation informatique 2D (3D). Passage d'un à plusieurs logiciels: compétence de choisir les outils adéquats en 2D et en 3D. Mise en relation des outils de CAO

CH-622: Synergism between Art of Total Synthesis and High Level Strategic Design (MOM)

Retro-synthessis, Total Synthesis, Atom-economy

HUM-220: Work and organizations

Comment travailler ensemble dans une start-up, un bureau d'étude ou une équipe restreinte ? Nous aborderons la question de l'organisation et des interactions au travail à travers des études de cas que

Disruptive selection

Disruptive selection, also called diversifying selection, describes changes in population genetics in which extreme values for a trait are favored over intermediate values. In this case, the variance of the trait increases and the population is divided into two distinct groups. In this more individuals acquire peripheral character value at both ends of the distribution curve. Natural selection is known to be one of the most important biological processes behind evolution.

Stabilizing selection

Negative selection (natural selection)

In natural selection, negative selection or purifying selection is the selective removal of alleles that are deleterious. This can result in stabilising selection through the purging of deleterious genetic polymorphisms that arise through random mutations. Purging of deleterious alleles can be achieved on the population genetics level, with as little as a single point mutation being the unit of selection. In such a case, carriers of the harmful point mutation have fewer offspring each generation, reducing the frequency of the mutation in the gene pool.

Neuro Robotics

At the same time, several different tutorials on available data and data tools, such as those from the Allen Institute for Brain Science, provide you with in-depth knowledge on brain atlases, gene exp

Neurorobotics

The MOOC on Neuro-robotics focuses on teaching advanced learners to design and construct a virtual robot and test its performance in a simulation using the HBP robotics platform. Learners will learn t

Neurorobotics

Vectorworks Educational Version

Introduces Vectorworks Educational Version for architectural drawings, covering tools, layers, and annotations.

Dose Management in Electron Microscopy

Explores the challenges and solutions for managing electron dose in microscopy, emphasizing the importance of accurate dose tracking and analysis.

Protein Abundance: Random Walks BIO-369: Randomness and information in biological data

Explores protein abundance as a random walk and the Moran model in population genetics.