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Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...
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While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.
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Basics of Multivariate Analysis in Neuroimaging Data
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Genomic Perspective on Multivariate Variation, Pleiotropy, and Evolution.

Diogo Melo1, Gabriel Marroig1, Jason B Wolf2

  • 1Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brasil.

The Journal of Heredity
|April 16, 2019
PubMed
Summary
This summary is machine-generated.

Researchers explored the genetic basis of evolutionary change in mice. They found that additive genetic effects drive divergence more than dominance effects, with pleiotropy influenced by selection and development.

Keywords:
G-matrixQTL mappinggenetic architecturegenome predictiongenotype–phenotype maphorseshoe prior

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Area of Science:

  • Quantitative genetics
  • Evolutionary biology
  • Genetics

Background:

  • Multivariate quantitative genetics is key to understanding phenotypic evolution and predicting evolutionary responses.
  • However, the genetic underpinnings of multivariate variation and evolutionary change remain poorly understood.
  • Empirical insights into how individual genetic effects generate genetic (co)variation are crucial.

Purpose of the Study:

  • To investigate the genetic architecture of multivariate phenotypic evolution.
  • To empirically link individual genetic effects to population-level evolutionary patterns.
  • To understand the role of pleiotropy in shaping genetic (co)variation and evolutionary divergence.

Main Methods:

  • Utilized an experimental mouse population derived from artificial selection lineages.
  • Developed a novel approach to estimate multivariate genetic effects of loci.
  • Characterized effect vectors by magnitude and alignment with evolutionary divergence.
  • Reconstructed ancestral traits and quantified genetic contributions to divergence.
  • Decomposed genetic covariation patterns and analyzed pleiotropic effects.

Main Results:

  • Additive genetic effects are substantially larger than dominance effects.
  • Additive effects are more strongly aligned with selection and divergence directions.
  • Larger additive effects exhibit greater alignment with divergence.
  • Pleiotropic effects are variable but generally modular.
  • Genetic effects align with selection, suggesting pleiotropy is shaped by evolutionary pressures.

Conclusions:

  • Additive genetic effects play a dominant role in multivariate evolutionary divergence.
  • Pleiotropy is a significant factor, influenced by both selection and developmental constraints.
  • This study provides a deeper empirical understanding of the genetic basis of evolutionary change.