The primary goal of<unk>  is to investigate the nature and origins of individual differences in behaviour. A wide variety of different methodological approaches are used in<unk> research, only a few of which are outlined below. Animal studies Investigators in animal behaviour genetics can carefully control for environmental factors and can experimentally manipulate genetic variants, allowing for a degree of causal inference that is not available in studies on human<unk> . In animal research selection experiments have often been employed. For example, laboratory house mice have been bred for open-field behaviour, thermoregulatory nesting, and voluntary wheel-running behaviour. A range of methods in these designs are covered on those pages.<unk> sts using model organisms employ a range of molecular techniques to alter, insert, or delete genes. These techniques include knockouts, floxing, gene knockdown, or genome editing using methods like CRISPR-Cas9. These techniques allow<unk> sts different levels of control in the model organism's genome, to evaluate the molecular, physiological, or<unk>  outcome of genetic changes. Animals commonly used as model organisms in<unk>  include mice, zebra fish, and the nematode species C. elegans. Twin and family studies Pedigree chart showing an inheritance pattern consistent with autosomal dominant transmission.<unk> sts have used pedigree studies to investigate the genetic and environmental basis of behaviour. Some research designs used in<unk> research are variations on family designs (also known as pedigree designs), including twin studies and adoption studies. Quantitative genetic modelling of individuals with known genetic relationships (e.g., parent-child, sibling, dizygotic and monozygotic twins) allows one to estimate to what extent genes and environment contribute to phenotypic differences among individuals. The basic intuition of the twin study is that monozygotic twins share 100% of their genome and dizygotic twins share, on average, 50% of their segregating genome. Thus, differences between the two members of a monozygotic twin pair can only be due to differences in their environment, whereas dizygotic twins will differ from one another due to environment as well as genes. Under this simplistic model, if dizygotic twins differ more than monozygotic twins it can only be attributable to genetic influences. An important assumption of the twin model is the equal environment assumption that monozygotic twins have the same shared environmental experiences as dizygotic twins. If, for example, monozygotic twins tend to have more similar experiences than dizygotic twins—and these experiences themselves are not genetically mediated through gene-environment correlation mechanisms—then monozygotic twins will tend to be more similar to one another than dizygotic twins for reasons that have nothing to do with genes. Twin studies of monozygotic and dizygotic twins use a biometrical formulation to describe the influences on twin similarity and to infer heritability. The formulation rests on the basic observation that the variance in a phenotype is due to two sources, genes and environment. More formally, , where is the phenotype, is the effect of genes, is the effect of the environment, and is a gene by environment interaction. The term can be expanded to include additive (), dominance (), and epistatic () genetic effects. Similarly, the environmental term can be expanded to include shared environment () and non-shared environment (), which includes any measurement error. Dropping the gene by environment interaction for simplicity (typical in twin studies) and fully decomposing the and terms, we now have . Twin research then models the similarity in monozygotic twins and dizogotic twins using simplified forms of this decomposition, shown in the table. + Decomposing the genetic and environmental contributions to twin similarity. Type of relationship Full decomposition Falconer's decomposition Perfect similarity between siblings Monozygotic twin correlation() Dizygotic twin correlation () Where is an unknown (probably very small) quantity. The simplified Falconer formulation can then be used to derive estimates of , , and . Rearranging and substituting the and equations one can obtain an estimate of the additive genetic variance, or heritability, , the non-shared environmental effect and, finally, the shared environmental effect . The Falconer formulation is presented here to illustrate how the twin model works. Modern approaches use maximum likelihood to estimate the genetic and environmental variance components. Measured genetic variants The Human Genome Project has allowed scientists to directly genotype the sequence of human DNA nucleotides. Once genotyped, genetic variants can be tested for association with a<unk>  phenotype, such as mental disorder, cognitive ability, personality, and so on. *Candidate Genes. One popular approach has been to test for association candidate genes with<unk>  phenotypes, where the candidate gene is selected based on some a priori theory about biological mechanisms involved in the manifestation of a<unk>  trait or phenotype. In general, such studies have proven difficult to broadly replicate and there has been concern raised that the false positive rate in this type of research is high. *Genome-wide association studies. In genome-wide association studies, researchers test the relationship of millions of genetic polymorphisms with<unk>  phenotypes across the genome. This approach to genetic association studies is largely atheoretical, and typically not guided by a particular biological hypothesis regarding the phenotype. Genetic association findings for<unk>  traits and psychiatric disorders have been found to be highly polygenic (involving many small genetic effects). *SNP heritability and co-heritability. Recently, researchers have begun to use similarity between classically unrelated people at their measured single nucleotide polymorphisms (SNPs) to estimate genetic variation or covariation that is tagged by SNPs, using mixed effects models implemented in software such as Genome-wide complex trait analysis (GCTA). To do this, researchers find the average genetic relatedness over all SNPs between all individuals in a (typically large) sample, and use Haseman–Elston regression or restricted maximum likelihood to estimate the genetic variation that is "tagged" by, or predicted by, the SNPs. The proportion of phenotypic variation that is accounted for by the genetic relatedness has been called "SNP heritability". Intuitively, SNP heritability increases to the degree that phenotypic similarity is predicted by genetic similarity at measured SNPs, and is expected to be lower than the true narrow-sense heritability to the degree that measured SNPs fail to tag (typically rare) causal variants. The value of this method is that it is an independent way to estimate heritability that does not require the same assumptions as those in twin and family studies, and that it gives insight into the allelic frequency spectrum of the causal variants underlying trait variation. Quasi-experimental designs Some<unk> designs are useful not to understand genetic influences on behaviour, but to control for genetic influences to test environmentally-mediated influences on behaviour. Such<unk> designs may be considered a subset of natural experiments, quasi-experiments that attempt to take advantage of naturally occurring situations that mimic true experiments by providing some control over an independent variable. Natural experiments can be particularly useful when experiments are infeasible, due to practical or ethical limitations. A general limitation of observational studies is that the relative influences of genes and environment are confounded. A simple demonstration of this fact is that measures of 'environmental' influence are heritable. Thus, observing a correlation between an environmental risk factor and a health outcome is not necessarily evidence for environmental influence on the health outcome. Similarly, in observational studies of parent-child<unk>  transmission, for example, it is impossible to know if the transmission is due to genetic or environmental influences, due to the problem of passive gene-environment correlation. The simple observation that the children of parents who use drugs are more likely to use drugs as adults does not indicate why the children are more likely to use drugs when they grow up. It could be because the children are modelling their parents' behaviour. Equally plausible, it could be that the children inherited drug-use-predisposing genes from their parent, which put them at increased risk for drug use as adults regardless of their parents' behaviour. Adoption studies, which parse the relative effects of rearing environment and genetic inheritance, find a small to negligible effect of rearing environment on smoking, alcohol, and marijuana use in adopted children, but a larger effect of rearing environment on harder drug use. Other<unk> designs include discordant twin studies, children of twins designs, and Mendelian randomization.
Behavioural genetics
Psychiatric genetics
Genomics
Genetics
Behavioral epigenetics
Developmental neuropsychology
Molecular medicine
Molecular genetics