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Background and Environment Affect Phenotype02:27

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Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
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Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
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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...
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In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
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Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Emerging semantics to link phenotype and environment.

Anne E Thessen1, Daniel E Bunker2, Pier Luigi Buttigieg3

  • 1Ronin Institute for Independent Scholarship , Monclair, NJ , United States ; The Data Detektiv , Waltham, MA , United States.

Peerj
|December 30, 2015
PubMed
Summary
This summary is machine-generated.

Linking biological phenotypes and environmental conditions is crucial for research. This study proposes using ontologies to standardize and integrate heterogeneous data, enabling advanced analyses in ecology and conservation biology.

Keywords:
BiodiversityData integrationEnvironmentOntologyPhenotypeSemantic web

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Area of Science:

  • Biology
  • Ecology
  • Conservation Biology
  • Phylogenetics

Background:

  • Phenotype-environment data are heterogeneous and difficult to integrate.
  • Standardizing and linking these data is essential for biological research.
  • Current ontologies have gaps and interoperability issues for phenotype-environment linkage.

Purpose of the Study:

  • To illustrate the need for robust phenotype-environment data linkage.
  • To demonstrate the value of integrating phenotype and environment data.
  • To propose data models for linking phenotypes and environments.

Main Methods:

  • Presented use cases from diverse biological disciplines.
  • Conducted proof-of-concept analyses on fishes and amphibians.
  • Proposed data models using the extensible observation ontology (OBOE) and Biological Collections Ontology (BCO).

Main Results:

  • Use cases highlight efficient answers to complex biological questions.
  • Proof-of-concept analyses demonstrate the utility of linking phenotype to environment data.
  • Developed example data models as a starting point for future development.

Conclusions:

  • Ontology-based data linkage is vital for advancing biological sciences.
  • Addressing ontological gaps and interoperability is key.
  • The proposed models offer a framework for integrating phenotype and environment data.