Single-Gene Influences on Brain and Behavior

Wahłsten, Douglas

doi:10.1146/annurev.psych.50.1.599

Cited by 69 publications

(34 citation statements)

References 98 publications

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“…Sometimes what appears to be precisely the opposite argument is made. That is, some would argue that global behavioral phenotypes (such as IQ) need no longer be subjected to quantitative genetic analysis because we already know genes are involved and we should focus at the single gene level (Wahlsten, 1999). Some critics argue that heritability studies are uninformative because heritability is a population sta-tistic that can vary dramatically from one place to another.…”

Section: Introduction-why Study the Relative Influence Of Heredity Anmentioning

confidence: 99%

Genetic and environmental influences on human psychological differences

2002

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Psychological researchers typically distinguish five major domains of individual differences in human behavior: cognitive abilities, personality, social attitudes, psychological interests, and psychopathology (Lubinski, 2000). In this article we: discuss a number of methodological errors commonly found in research on human individual differences; introduce a broad framework for interpreting findings from contemporary behavioral genetic studies; briefly outline the basic quantitative methods used in human behavioral genetic research; review the major criticisms of behavior genetic designs, with particular emphasis on the twin and adoption methods; describe the major or dominant theoretical scheme in each domain; and review behavioral genetic findings in all five domains. We conclude that there is now strong evidence that virtually all individual psychological differences, when reliably measured, are moderately to substantially heritable.

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Section: Introduction-why Study the Relative Influence Of Heredity Anmentioning

confidence: 99%

Genetic and environmental influences on human psychological differences

2002

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“…Many behaviors of great importance to society and public health are influenced substantially by genes, and, furthermore, are genetically complex (Wahlsten, 1999). These behaviors include abusive patterns of self-administration of alcohol and other drugs (Crabbe, 2002) as well as other psychiatric disorders such as depression, impulsivity, and schizophrenia (Moldin and Gottesman, 1997;.…”

Section: Introductionmentioning

confidence: 99%

Different data from different labs: Lessons from studies of gene–environment interaction

et al. 2002

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ABSTRACT:It is sometimes supposed that standardizing tests of mouse behavior will ensure similar results in different laboratories. We evaluated this supposition by conducting behavioral tests with identical apparatus and test protocols in independent laboratories. Eight genetic groups of mice, including equal numbers of males and females, were either bred locally or shipped from the supplier and then tested on six behaviors simultaneously in three laboratories (Albany, NY; Edmonton, AB; Portland, OR). The behaviors included locomotor activity in a small box, the elevated plus maze, accelerating rotarod, visible platform water escape, cocaine activation of locomotor activity, and ethanol preference in a twobottle test. A preliminary report of this study presented a conventional analysis of conventional measures that revealed strong effects of both genotype and laboratory as well as noteworthy interactions between genotype and laboratory. We now report a more detailed analysis of additional measures and view the data for each test in different ways. Whether mice were shipped from a supplier or bred locally had negligible effects for almost every measure in the six tests, and sex differences were also absent or very small for most behaviors, whereas genetic effects were almost always large. For locomotor activity, cocaine activation, and elevated plus maze, the analysis demonstrated the strong dependence of genetic differences in behavior on the laboratory giving the tests. For ethanol preference and water escape learning, on the other hand, the three labs obtained essentially the same results for key indicators of behavior. Thus, it is clear that the strong dependence of results on the specific laboratory is itself dependent on the task in question. Our results suggest that there may be advantages of test standardization, but laboratory environments probably can never be made sufficiently similar to guarantee identical results on a wide range of tests in a wide range of labs. Interpretations of our results by colleagues in neuroscience as well as the mass media are reviewed. Pessimistic views, prevalent in the media but relatively uncommon among neuroscientists, of mouse behavioral tests as being highly unreliable are contradicted by our data. Despite the presence of noteworthy interactions between genotype and lab environment, most of the larger differences between inbred strains were replicated across the three labs. Strain differences of moderate effects size, on the other hand, often differed markedly among labs, especially those involving three 129-derived strains. Implications for behavioral screening of targeted and induced mutations in mice are discussed.

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“…Most of these genes have functions that are central to the brain, where GBM occurs. AGAP2 is an Arf GAP that has anti-apoptotic effects of nerve growth factor (Inoue and Randazzo, 2007), CRY2 is a circadian rhythm gene that principally is localized in the brain, GRIN1 is a ligand-gated ion channel that facilitates signals through neurons (Wahlsten, 1999). UPF3A is found in the UPF complex that is implicated in pathways altered in cancer such as post-splicing, mRNA decay and nuclear export (Dreyfuss et al, 2002).…”

Section: Known and Novel Targetsmentioning

confidence: 99%

The discordant method: a novel approach for differential correlation

2015

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Motivation: Current differential correlation methods are designed to determine molecular feature pairs that have the largest magnitude of difference between correlation coefficients. These methods do not easily capture molecular feature pairs that experience no correlation in one group but correlation in another, which may reflect certain types of biological interactions. We have developed a tool, the Discordant method, which categorizes the correlation types for each group to make this possible. Results: We compare the Discordant method to existing approaches using simulations and two biological datasets with different types of -omics data. In contrast to other methods, Discordant identifies phenotype-related features at a similar or higher rate while maintaining reasonable computational tractability and usability. Availability and implementation: R code and sample data are available at https://github.com/siskac/

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Single-Gene Influences on Brain and Behavior

Cited by 69 publications

References 98 publications

Genetic and environmental influences on human psychological differences

Genetic and environmental influences on human psychological differences

Different data from different labs: Lessons from studies of gene–environment interaction

The discordant method: a novel approach for differential correlation

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