Identification and ranking of genetic and laboratory environment factors influencing a behavioral trait, thermal nociception, via computational analysis of a large data archive

Laboratory conditions in biobehavioral experiments are commonly assumed to be ‘controlled’, having little impact on the outcome. However, recent studies have illustrated that the laboratory environment has a robust effect on behavioral traits. Given that environmental factors can interact with trait...

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Published in:Neuroscience and Biobehavioral Reviews Vol. 26; no. 8; pp. 907 - 923
Main Authors: Chesler, Elissa J, Wilson, Sonya G, Lariviere, William R, Rodriguez-Zas, Sandra L, Mogil, Jeffrey S
Format: Book Review Journal Article
Language:English
Published: Oxford Elsevier Ltd 01-12-2002
Elsevier
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Abstract Laboratory conditions in biobehavioral experiments are commonly assumed to be ‘controlled’, having little impact on the outcome. However, recent studies have illustrated that the laboratory environment has a robust effect on behavioral traits. Given that environmental factors can interact with trait-relevant genes, some have questioned the reliability and generalizability of behavior genetic research designed to identify those genes. This problem might be alleviated by the identification of the most relevant environmental factors, but the task is hindered by the large number of factors that typically vary between and within laboratories. We used a computational approach to retrospectively identify and rank sources of variability in nociceptive responses as they occurred in a typical research laboratory over several years. A machine-learning algorithm was applied to an archival data set of 8034 independent observations of baseline thermal nociceptive sensitivity. This analysis revealed that a factor even more important than mouse genotype was the experimenter performing the test, and that nociception can be affected by many additional laboratory factors including season/humidity, cage density, time of day, sex and within-cage order of testing. The results were confirmed by linear modeling in a subset of the data, and in confirmatory experiments, in which we were able to partition the variance of this complex trait among genetic (27%), environmental (42%) and genetic×environmental (18%) sources.
AbstractList Laboratory conditions in biobehavioral experiments are commonly assumed to be 'controlled', having little impact on the outcome. However, recent studies have illustrated that the laboratory environment has a robust effect on behavioral traits. Given that environmental factors can interact with trait-relevant genes, some have questioned the reliability and generalizability of behavior genetic research designed to identify those genes. This problem might be alleviated by the identification of the most relevant environmental factors, but the task is hindered by the large number of factors that typically vary between and within laboratories. We used a computational approach to retrospectively identify and rank sources of variability in nociceptive responses as they occurred in a typical research laboratory over several years. A machine-learning algorithm was applied to an archival data set of 8034 independent observations of baseline thermal nociceptive sensitivity. This analysis revealed that a factor even more important than mouse genotype was the experimenter performing the test, and that nociception can be affected by many additional laboratory factors including season/humidity, cage density, time of day, sex and within-cage order of testing. The results were confirmed by linear modeling in a subset of the data, and in confirmatory experiments, in which we were able to partition the variance of this complex trait among genetic (27%), environmental (42%) and genetic x environmental (18%) sources.
Laboratory conditions in biobehavioral experiments are commonly assumed to be ‘controlled’, having little impact on the outcome. However, recent studies have illustrated that the laboratory environment has a robust effect on behavioral traits. Given that environmental factors can interact with trait-relevant genes, some have questioned the reliability and generalizability of behavior genetic research designed to identify those genes. This problem might be alleviated by the identification of the most relevant environmental factors, but the task is hindered by the large number of factors that typically vary between and within laboratories. We used a computational approach to retrospectively identify and rank sources of variability in nociceptive responses as they occurred in a typical research laboratory over several years. A machine-learning algorithm was applied to an archival data set of 8034 independent observations of baseline thermal nociceptive sensitivity. This analysis revealed that a factor even more important than mouse genotype was the experimenter performing the test, and that nociception can be affected by many additional laboratory factors including season/humidity, cage density, time of day, sex and within-cage order of testing. The results were confirmed by linear modeling in a subset of the data, and in confirmatory experiments, in which we were able to partition the variance of this complex trait among genetic (27%), environmental (42%) and genetic×environmental (18%) sources.
Author Rodriguez-Zas, Sandra L
Mogil, Jeffrey S
Lariviere, William R
Wilson, Sonya G
Chesler, Elissa J
Author_xml – sequence: 1
  givenname: Elissa J
  surname: Chesler
  fullname: Chesler, Elissa J
  organization: Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
– sequence: 2
  givenname: Sonya G
  surname: Wilson
  fullname: Wilson, Sonya G
  organization: Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
– sequence: 3
  givenname: William R
  surname: Lariviere
  fullname: Lariviere, William R
  organization: Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
– sequence: 4
  givenname: Sandra L
  surname: Rodriguez-Zas
  fullname: Rodriguez-Zas, Sandra L
  organization: Department of Animal Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
– sequence: 5
  givenname: Jeffrey S
  surname: Mogil
  fullname: Mogil, Jeffrey S
  email: jeffrey.mogil@mcgill.ca
  organization: Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA
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Issue 8
Keywords Nociception
Pain
Genetic
Environment
Mice
Data mining
CART
Noxious stimulus
Methodology
Rodentia
Thermal stimulus
Environmental factor
Review
Genetic determinism
Ambient humidity
Strain
Vertebrata
Mammalia
Investigation method
Mouse
Animal
Sexual dimorphism
Comparative study
Language English
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PublicationTitle Neuroscience and Biobehavioral Reviews
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Snippet Laboratory conditions in biobehavioral experiments are commonly assumed to be ‘controlled’, having little impact on the outcome. However, recent studies have...
Laboratory conditions in biobehavioral experiments are commonly assumed to be 'controlled', having little impact on the outcome. However, recent studies have...
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SubjectTerms Animals
Archives
Automatic Data Processing
Behavior - physiology
Biological and medical sciences
CART
Computational Biology
Data mining
Environment
Female
Fundamental and applied biological sciences. Psychology
Genetic
Genetics
Genotype
Laboratories
Male
Mice
Mice, Inbred Strains
Models, Genetic
Nociception
Pain
Pain Measurement
Perception
Proprioception. Interoception. Pain perception
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Quantitative Trait, Heritable
Seasons
Species Specificity
Title Identification and ranking of genetic and laboratory environment factors influencing a behavioral trait, thermal nociception, via computational analysis of a large data archive
URI https://dx.doi.org/10.1016/S0149-7634(02)00103-3
https://www.ncbi.nlm.nih.gov/pubmed/12667496
https://search.proquest.com/docview/72875716
Volume 26
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