Behavioural genetics

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Selective breeding and the domestication of animals is perhaps the earliest evidence that humans considered the idea that individual differences in behaviour could be due to natural causes.{{cite book | vauthors = Loehlin JC | title= Handbook of Behavior Genetics | chapter= History of Behavior Genetics | date= 2009 | pages= 3–11 | veditors =Kim Y | doi = 10.1007/978-0-387-76727-7_1 | publisher = Springer | location = New York, NY | isbn = 978-0-387-76726-0 | edition = 1 }} Plato and Aristotle each speculated on the basis and mechanisms of inheritance of behavioural characteristics.{{cite book | veditors = Jones BC, Mormede P | title = Neurobehavioral Genetics: Methods and Applications, Second Edition|chapter=A History of Behavior Genetics| vauthors = Maxson SC | chapter-url=https://books.google.com/books?id=P85FPhRKFVMC&pg=PA15 | date=30 August 2006 | publisher=CRC Press | isbn = 978-1-4200-0356-7 }} Plato, for example, argued in The Republic that selective breeding among the citizenry to encourage the development of some traits and discourage others, what today might be called eugenics, was to be encouraged in the pursuit of an ideal society. Behavioural genetic concepts also existed during the English Renaissance, where William Shakespeare perhaps first coined the phrase "nature versus nurture" in The Tempest, where he wrote in Act IV, Scene I, that Caliban was "A devil, a born devil, on whose nature Nurture can never stick".{{cite book | title = The Tempest|series=The Arden Shakespeare | edition = Third | vauthors = Vaughan V, Vaughan AT | publisher =The Arden Shakespeare | year = 1999 | isbn = 978-1-903436-08-0 | page = 60 }}

Modern-day behavioural genetics began with Sir Francis Galton, a nineteenth-century intellectual and cousin of Charles Darwin.{{cite encyclopedia | vauthors = McGue M, Gottesman II | encyclopedia = The Encyclopedia of Clinical Psychology | year = 2015 | pages = 1–11 | doi = 10.1002/9781118625392.wbecp578 | isbn = 9781118625392 | chapter = Behavior Genetics }} Galton was a polymath who studied many subjects, including the heritability of human abilities and mental characteristics. One of Galton's investigations involved a large pedigree study of social and intellectual achievement in the English upper class. In 1869, 10 years after Darwin's On the Origin of Species, Galton published his results in Hereditary Genius.{{cite book |title=Hereditary Genius: An Inquiry into Its Laws and Consequences |url=http://galton.org/books/hereditary-genius/ |year=1869 |location=London |publisher=MacMillan and Co. |access-date=17 December 2009 |archive-url=https://web.archive.org/web/20191207132222/http://galton.org/books/hereditary-genius/ |archive-date=7 December 2019 |url-status=dead }} In this work, Galton found that the rate of "eminence" was highest among close relatives of eminent individuals, and decreased as the degree of relationship to eminent individuals decreased. While Galton could not rule out the role of environmental influences on eminence, a fact which he acknowledged, the study served to initiate an important debate about the relative roles of genes and environment on behavioural characteristics. Through his work, Galton also "introduced multivariate analysis and paved the way towards modern Bayesian statistics" that are used throughout the sciences—launching what has been dubbed the "Statistical Enlightenment".{{cite journal | vauthors = Stigler SM | title = Darwin, Galton and the Statistical Enlightenment | journal = Journal of the Royal Statistical Society, Series A | volume = 173 | issue = 3 | pages = 469–482 |date=July 2010 | doi = 10.1111/j.1467-985X.2010.00643.x | s2cid = 53333238 }}

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The field of behavioural genetics, as founded by Galton, was ultimately undermined by another of Galton's intellectual contributions, the founding of the eugenics movement in 20th century society. The primary idea behind eugenics was to use selective breeding combined with knowledge about the inheritance of behaviour to improve the human species. The eugenics movement was subsequently discredited by scientific corruption and genocidal actions in Nazi Germany. Behavioural genetics was thereby discredited through its association to eugenics. The field once again gained status as a distinct scientific discipline through the publication of early texts on behavioural genetics, such as Calvin S. Hall's 1951 book chapter on behavioural genetics, in which he introduced the term "psychogenetics",{{cite book | author = Hall CS |chapter = The genetics of behavior | editor = Stevens SS | title = Handbook of Experimental Psychology | publisher = John Wiley and Sons | location = New York | date = 1951 | pages = 304–329}} which enjoyed some limited popularity in the 1960s and 1970s.{{cite book | vauthors = Grigorenko EL, Ravich-Shcherbo I | chapter = Russian psychogenetics | veditors = Grigorenko EL | title = Psychology of Russia: Past, Present, Future | publisher = Nova Science | location = Commack, NY | date = 1997 | pages = 83–124 }}{{cite journal | vauthors = Broadhurst PL | title = Psychogenetics of emotionality in the rat | journal = Annals of the New York Academy of Sciences | volume = 159 | issue = 3 | pages = 806–24 | date = July 1969 | pmid = 5260300 | doi = 10.1111/j.1749-6632.1969.tb12980.x | bibcode = 1969NYASA.159..806B | s2cid = 42323956 }} However, it eventually disappeared from usage in favour of "behaviour genetics".

The start of behaviour genetics as a well-identified field was marked by the publication in 1960 of the book Behavior Genetics by John L. Fuller and William Robert (Bob) Thompson.{{cite book | vauthors = Fuller JL, Thompson WR | title = Behavior Genetics | publisher = John Wiley and Sons | location = New York | date = 1960 }} It is widely accepted now that many if not most behaviours in animals and humans are under significant genetic influence, although the extent of genetic influence for any particular trait can differ widely.{{cite journal| vauthors= Turkheimer E| date= 2000| title= Three Laws of Behavior Genetics and What They Mean| url= http://www.psychologicalscience.org/newsresearch/publications/journals/currdir/cd9_5_5.pdf| journal= Current Directions in Psychological Science| volume= 9| issue= 5| pages= 160–164| doi= 10.1111/1467-8721.00084| s2cid= 2861437| access-date= 2016-04-12| archive-date= 2016-10-09| archive-url= https://web.archive.org/web/20161009084457/http://www.psychologicalscience.org/newsresearch/publications/journals/currdir/cd9_5_5.pdf| url-status= live}} A decade later, in February 1970, the first issue of the journal Behavior Genetics was published and in 1972 the Behavior Genetics Association was formed with Theodosius Dobzhansky elected as the association's first president. The field has since grown and diversified, touching many scientific disciplines.{{cite journal | vauthors = Ayorech Z, Selzam S, Smith-Woolley E, Knopik VS, Neiderhiser JM, DeFries JC, Plomin R | title = Publication Trends Over 55 Years of Behavioral Genetic Research | journal = Behavior Genetics | volume = 46 | issue = 5 | pages = 603–7 | date = September 2016 | pmid = 26992731 | pmc = 5206393 | doi = 10.1007/s10519-016-9786-2 }}

The primary goal of behavioural genetics is to investigate the nature and origins of individual differences in behaviour. A wide variety of different methodological approaches are used in behavioural genetic research,{{cite book | vauthors = Plomin R, DeFries JC, Knopik VS, Neiderhiser M | title = Behavioral Genetics | url = https://books.google.com/books?id=OytMMAEACAAJ | date = 24 September 2012 | publisher = Worth Publishers | isbn = 978-1-4292-4215-8 | access-date = 27 January 2016 | archive-date = 31 December 2013 | archive-url = https://web.archive.org/web/20131231103724/http://books.google.com/books?id=OytMMAEACAAJ | url-status = live }} only a few of which are outlined below.

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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 behavioural genetics.{{Cite encyclopedia |title=Behaviour genetics |url=https://www.britannica.com/science/behaviour-genetics | vauthors=Plomin R |author-link=Robert Plomin |language=en | encyclopedia =Encyclopedia Britannica |access-date=15 June 2018 |archive-date=17 April 2021 |archive-url=https://web.archive.org/web/20210417115212/https://www.britannica.com/science/behaviour-genetics |url-status=live }} In animal research selection experiments have often been employed. For example, laboratory house mice have been bred for open-field behaviour,{{cite journal | vauthors=DeFries JC, Hegmann JP, Halcomb RA | title=Response to 20 generations of selection for open-field activity in mice | journal=Behavioral Biology | volume=11 | issue=4 | pages=481–95 | date=August 1974 | pmid=4415597 | doi=10.1016/s0091-6773(74)90800-1 }} thermoregulatory nesting,{{cite journal | vauthors=Lynch CB | title=Response to divergent selection for nesting behavior in Mus musculus | journal=Genetics | volume=96 | issue=3 | pages=757–65 | date=November 1980 | doi=10.1093/genetics/96.3.757 | pmid=7196362 | pmc=1214374 }} and voluntary wheel-running behaviour.{{cite journal | vauthors=Swallow JG, Carter PA, Garland T | title=Artificial selection for increased wheel-running behavior in house mice | journal=Behavior Genetics | volume=28 | issue=3 | pages=227–37 | date=May 1998 | pmid=9670598 | doi=10.1023/A:1021479331779 | s2cid=18336243 | author3-link=Theodore Garland, Jr. }} A range of methods in these designs are covered on those pages.

Behavioural geneticists 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.{{cite journal | vauthors=Heidenreich M, Zhang F | title=Applications of CRISPR-Cas systems in neuroscience | journal=Nature Reviews. Neuroscience | volume=17 | issue=1 | pages=36–44 | date=January 2016 | pmid=26656253 | pmc=4899966 | doi=10.1038/nrn.2015.2 }} These techniques allow behavioural geneticists different levels of control in the model organism's genome, to evaluate the molecular, physiological, or behavioural outcome of genetic changes.{{cite journal | vauthors=Singh P, Schimenti JC, Bolcun-Filas E | title=A mouse geneticist's practical guide to CRISPR applications | journal=Genetics | volume=199 | issue=1 | pages=1–15 | date=January 2015 | pmid=25271304 | pmc=4286675 | doi=10.1534/genetics.114.169771 }} Animals commonly used as model organisms in behavioural genetics include mice,{{cite journal | vauthors=Cryan JF, Holmes A | title=The ascent of mouse: advances in modelling human depression and anxiety | language=En | journal=Nature Reviews. Drug Discovery | volume=4 | issue=9 | pages=775–790 | date=September 2005 | pmid=16138108 | doi=10.1038/nrd1825 | s2cid=18207374 }} zebra fish,{{cite journal | vauthors=Wolman M, Granato M | title=Behavioral genetics in larval zebrafish: learning from the young | journal=Developmental Neurobiology | volume=72 | issue=3 | pages=366–372 | date=March 2012 | pmid=22328273 | pmc=6430578 | doi=10.1002/dneu.20872 }} Drosophila,{{Cite journal |last1=Anholt |first1=Robert RH |last2=Mackay |first2=Trudy FC |date=2015-04-01 |title=Dissecting the genetic architecture of behavior in Drosophila melanogaster |journal=Current Opinion in Behavioral Sciences |volume=2 |pages=1–7 |doi=10.1016/j.cobeha.2014.06.001 |pmid=26203460 |pmc=4507818}} and the nematode species C. elegans.{{cite journal | vauthors=Wolinsky E, Way J | title=The behavioral genetics of Caenorhabditis elegans | journal=Behavior Genetics | volume=20 | issue=2 | pages=169–189 | date=March 1990 | pmid=2191646 | doi=10.1007/bf01067789 | s2cid=23719167 }}

Machine learning and A.I. developments are allowing researchers to design experiments that are able to manage the complexity and large data sets generated, allowing for increasingly complex behavioural experiments.{{cite journal | vauthors=Stacher Hörndli CN, Wong E, Ferris E, Bennett K, Steinwand S, Rhodes AN, Fletcher PT, Gregg C | title=Complex Economic Behavior Patterns Are Constructed from Finite, Genetically Controlled Modules of Behavior | journal=Cell Reports | volume=28 | issue=7 | pages=1814–1829.e6 | date=August 2019 | pmid=31412249 | pmc=7476553 | doi=10.1016/j.celrep.2019.07.038 | s2cid=199662477 }}

{{Main|Human behaviour genetics}}

{{See also|Heritability|Quantitative genetics#Pedigree analysis}}

Some research designs used in behavioural genetic 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.{{cite book| vauthors = Falconer DS |title=Introduction to quantitative genetics|url=https://books.google.com/books?id=on_wAAAAMAAJ|year=1989|publisher=Longman, Scientific & Technical|isbn=978-0-470-21162-5|access-date=2016-12-02|archive-date=2021-04-22|archive-url=https://web.archive.org/web/20210422170352/https://books.google.com/books?id=on_wAAAAMAAJ|url-status=live}}

{{Main|Twin studies}}

File:Autosomal Dominant Pedigree Chart2.svg showing an inheritance pattern consistent with autosomal dominant transmission. Behavioural geneticists have used pedigree studies to investigate the genetic and environmental basis of behaviour.]]

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 genes in addition to the environment. 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{{cite journal | vauthors = Eaves L, Foley D, Silberg J | title = Has the "Equal Environments" assumption been tested in twin studies? | journal = Twin Research | volume = 6 | issue = 6 | pages = 486–9 | year = 2003 | pmid = 14965458 | doi = 10.1375/136905203322686473 | doi-access = free }} 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.{{cite journal | vauthors = Kendler KS, Neale MC, Kessler RC, Heath AC, Eaves LJ | title = A test of the equal-environment assumption in twin studies of psychiatric illness | journal = Behavior Genetics | volume = 23 | issue = 1 | pages = 21–7 | date = January 1993 | pmid = 8476388 | doi = 10.1007/BF01067551 | citeseerx = 10.1.1.595.7413 | s2cid = 9034050 }} While this assumption should be kept in mind when interpreting the results of twin studies, research tends to support the equal environment assumption.{{Cite book | vauthors = Harden KP |url=https://books.google.com/books?id=WdoiEAAAQBAJ&dq=harden+genetic+lottery&pg=PA27 |title=The Genetic Lottery: Why DNA Matters for Social Equality |date=2021-09-21 |publisher=Princeton University Press |isbn=978-0-691-22670-5 |pages=276 |language=en}}

Twin studies of monozygotic and dizygotic twins use a biometrical formulation to describe the influences on twin similarity and to infer heritability.{{cite journal |vauthors= Jinks JL, Fulker DW | date= 1970| title= Comparison of the biometrical genetical, MAVA, and classical approaches to the analysis of the human behavior. |journal= Psychological Bulletin | volume=73| issue= 5|pages=311–349|doi= 10.1037/h0029135 | pmid=5528333}}

The formulation rests on the basic observation that the variance in a phenotype is due to two sources, genes and environment. More formally, $Var(P)\; =\; g\; +\; (g\; \backslash times\; \backslash epsilon)\; +\; \backslash epsilon$, where $P$ is the phenotype, $g$ is the effect of genes, $\backslash epsilon$ is the effect of the environment, and $(g\; \backslash times\; \backslash epsilon)$ is a gene by environment interaction. The $g$ term can be expanded to include additive ($a^2$), dominance ($d^2$), and epistatic ($i^2$) genetic effects. Similarly, the environmental term $\backslash epsilon$ can be expanded to include shared environment ($c^2$) and non-shared environment ($e^2$), which includes any measurement error. Dropping the gene by environment interaction for simplicity (typical in twin studies) and fully decomposing the $g$ and $\backslash epsilon$ terms, we now have $Var(P)\; =\; (a^2\; +\; d^2\; +\; i^2)\; +\; (c^2\; +\; e^2)$. Twin research then models the similarity in monozygotic twins and dizygotic twins using simplified forms of this decomposition, shown in the table.

The simplified Falconer formulation can then be used to derive estimates of $a^2$, $c^2$, and $e^2$. Rearranging and substituting the $r\_\{MZ\}$ and $r\_\{DZ\}$ equations one can obtain an estimate of the additive genetic variance, or heritability, $a^2\; =\; 2(r\_\{MZ\}\; -\; r\_\{DZ\})$, the non-shared environmental effect $e^2\; =\; 1-\; r\_\{MZ\}$ and, finally, the shared environmental effect $c^2\; =\; 2r\_\{DZ\}\; -\; r\_\{MZ\}$. 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.{{cite journal | vauthors = Martin NG, Eaves LJ | title = The genetical analysis of covariance structure | journal = Heredity | volume = 38 | issue = 1 | pages = 79–95 | date = February 1977 | pmid = 268313 | doi = 10.1038/hdy.1977.9 | doi-access = free }}

The Human Genome Project has allowed scientists to directly genotype the sequence of human DNA nucleotides.{{cite journal | vauthors = Lander ES | title = Initial impact of the sequencing of the human genome | journal = Nature | volume = 470 | issue = 7333 | pages = 187–97 | date = February 2011 | pmid = 21307931 | doi = 10.1038/nature09792 | bibcode = 2011Natur.470..187L | hdl = 1721.1/69154 | s2cid = 4344403 | hdl-access = free }} Once genotyped, genetic variants can be tested for association with a behavioural phenotype, such as mental disorder, cognitive ability, personality, and so on.{{cite journal | vauthors = McCarthy MI, Abecasis GR, Cardon LR, Goldstein DB, Little J, Ioannidis JP, Hirschhorn JN | title = Genome-wide association studies for complex traits: consensus, uncertainty and challenges | journal = Nature Reviews Genetics | volume = 9 | issue = 5 | pages = 356–69 | date = May 2008 | pmid = 18398418 | doi = 10.1038/nrg2344 | s2cid = 15032294 }}

• Candidate Genes. One popular approach has been to test for association candidate genes with behavioural phenotypes, where the candidate gene is selected based on some a priori theory about biological mechanisms involved in the manifestation of a behavioural trait or phenotype. In general, such studies have proven difficult to broadly replicate{{cite journal | vauthors = Farrell MS, Werge T, Sklar P, Owen MJ, Ophoff RA, O'Donovan MC, Corvin A, Cichon S, Sullivan PF | title = Evaluating historical candidate genes for schizophrenia | journal = Molecular Psychiatry | volume = 20 | issue = 5 | pages = 555–562 | date = May 2015 | pmid = 25754081 | pmc = 4414705 | doi = 10.1038/mp.2015.16 }}{{cite journal | vauthors = Hewitt JK | title = Editorial policy on candidate gene association and candidate gene-by-environment interaction studies of complex traits | journal = Behavior Genetics | volume = 42 | issue = 1 | pages = 1–2 | date = January 2012 | pmid = 21928046 | doi = 10.1007/s10519-011-9504-z | s2cid = 11492871 }}{{cite journal | vauthors = Johnson EC, Border R, Melroy-Greif WE, de Leeuw CA, Ehringer MA, Keller MC | title = No Evidence That Schizophrenia Candidate Genes Are More Associated With Schizophrenia Than Noncandidate Genes | journal = Biological Psychiatry | volume = 82 | issue = 10 | pages = 702–708 | date = November 2017 | pmid = 28823710 | pmc = 5643230 | doi = 10.1016/j.biopsych.2017.06.033 | series = Risk Genes and the Emergence of Schizophrenia }}{{cite journal | vauthors = Border R, Johnson EC, Evans LM, Smolen A, Berley N, Sullivan PF, Keller MC | title = No Support for Historical Candidate Gene or Candidate Gene-by-Interaction Hypotheses for Major Depression Across Multiple Large Samples | journal = The American Journal of Psychiatry | volume = 176 | issue = 5 | pages = 376–387 | date = May 2019 | pmid = 30845820 | pmc = 6548317 | doi = 10.1176/appi.ajp.2018.18070881 }} and there has been concern raised that the false positive rate in this type of research is high.{{cite journal | vauthors = Colhoun HM, McKeigue PM, Davey Smith G | title = Problems of reporting genetic associations with complex outcomes | journal = Lancet | volume = 361 | issue = 9360 | pages = 865–872 | date = March 2003 | pmid = 12642066 | doi = 10.1016/S0140-6736(03)12715-8 | s2cid = 15679561 }}

• Genome-wide association studies In genome-wide association studies, researchers test the relationship of millions of genetic polymorphisms with behavioural 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 behavioural traits and psychiatric disorders have been found to be highly polygenic (involving many small genetic effects).{{cite journal | vauthors = Visscher PM, Brown MA, McCarthy MI, Yang J | title = Five years of GWAS discovery | journal = American Journal of Human Genetics | volume = 90 | issue = 1 | pages = 7–24 | date = January 2012 | pmid = 22243964 | pmc = 3257326 | doi = 10.1016/j.ajhg.2011.11.029 }}{{cite journal | vauthors = Ripke S, Neale BM, Corvin A, Walters JT, Farh KH, Holmans PA, etal | collaboration = Schizophrenia Working Group of the Psychiatric Genomics Consortium | title = Biological insights from 108 schizophrenia-associated genetic loci | journal = Nature | volume = 511 | issue = 7510 | pages = 421–7 | date = July 2014 | pmid = 25056061 | pmc = 4112379 | doi = 10.1038/nature13595 | bibcode = 2014Natur.511..421S}}{{cite journal | vauthors = Lee SH, DeCandia TR, Ripke S, Yang J, Sullivan PF, Goddard ME, Keller MC, Visscher PM, Wray NR | title = Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs | journal = Nature Genetics | volume = 44 | issue = 3 | pages = 247–50 | date = February 2012 | pmid = 22344220 | pmc = 3327879 | doi = 10.1038/ng.1108 }}{{cite journal | vauthors = Sullivan PF, Daly MJ, O'Donovan M | title = Genetic architectures of psychiatric disorders: the emerging picture and its implications | journal = Nature Reviews. Genetics | volume = 13 | issue = 8 | pages = 537–51 | date = July 2012 | pmid = 22777127 | pmc = 4110909 | doi = 10.1038/nrg3240 }} File:Genetic correlation results about traits, IQ and language skills.jpgs appear to be influenced by genetics{{cite news |title=Massive genome study informs the biology of reading and language |url=https://medicalxpress.com/news/2022-08-massive-genome-biology-language.html |access-date=18 September 2022 |work=Max Planck Society via medicalxpress.com |language=en}}{{cite journal | vauthors = Eising E, Mirza-Schreiber N, de Zeeuw EL, Wang CA, Truong DT, Allegrini AG, Shapland CY, Zhu G, Wigg KG, Gerritse ML, Molz B, Alagöz G, Gialluisi A, Abbondanza F, Rimfeld K, van Donkelaar M, Liao Z, Jansen PR, Andlauer TF, Bates TC, Bernard M, Blokland K, Bonte M, Børglum AD, Bourgeron T, Brandeis D, Ceroni F, Csépe V, Dale PS, de Jong PF, DeFries JC, Démonet JF, Demontis D, Feng Y, Gordon SD, Guger SL, Hayiou-Thomas ME, Hernández-Cabrera JA, Hottenga JJ, Hulme C, Kere J, Kerr EN, Koomar T, Landerl K, Leonard GT, Lovett MW, Lyytinen H, Martin NG, Martinelli A, Maurer U, Michaelson JJ, Moll K, Monaco AP, Morgan AT, Nöthen MM, Pausova Z, Pennell CE, Pennington BF, Price KM, Rajagopal VM, Ramus F, Richer L, Simpson NH, Smith SD, Snowling MJ, Stein J, Strug LJ, Talcott JB, Tiemeier H, van der Schroeff MP, Verhoef E, Watkins KE, Wilkinson M, Wright MJ, Barr CL, Boomsma DI, Carreiras M, Franken MJ, Gruen JR, Luciano M, Müller-Myhsok B, Newbury DF, Olson RK, Paracchini S, Paus T, Plomin R, Reilly S, Schulte-Körne G, Tomblin JB, van Bergen E, Whitehouse AJ, Willcutt EG, St Pourcain B, Francks C, Fisher SE | title = Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 119 | issue = 35 | pages = e2202764119 | date = August 2022 | pmid = 35998220 | pmc = 9436320 | doi = 10.1073/pnas.2202764119 | bibcode = 2022PNAS..11902764E | doi-access = free }}]] Genetic variants identified to be associated with some trait or disease through GWAS may be used to improve disease risk predictions. However, the genetic variants identified through GWAS of common genetic variants are most likely to have a modest effect on disease risk or development of a given trait. This is different from the strong genetic contribution seen in Mendelian conditions or for some rare variants that may have a larger effect on disease.

• 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).{{cite journal | vauthors = Yang J, Benyamin B, McEvoy BP, Gordon S, Henders AK, Nyholt DR, Madden PA, Heath AC, Martin NG, Montgomery GW, Goddard ME, Visscher PM | title = Common SNPs explain a large proportion of the heritability for human height | journal = Nature Genetics | volume = 42 | issue = 7 | pages = 565–9 | date = July 2010 | pmid = 20562875 | pmc = 3232052 | doi = 10.1038/ng.608 }} 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".{{cite journal | vauthors = Lee SH, Yang J, Chen GB, Ripke S, Stahl EA, Hultman CM, Sklar P, Visscher PM, Sullivan PF, Goddard ME, Wray NR | title = Estimation of SNP heritability from dense genotype data | journal = American Journal of Human Genetics | volume = 93 | issue = 6 | pages = 1151–5 | year = 2013 | pmid = 24314550 | pmc = 3852919 | doi = 10.1016/j.ajhg.2013.10.015 }} 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.{{cite journal | vauthors = Visscher PM, Yang J, Goddard ME | title = A commentary on 'common SNPs explain a large proportion of the heritability for human height' by Yang et al. (2010) | journal = Twin Research and Human Genetics | volume = 13 | issue = 6 | pages = 517–24 | year = 2010 | pmid = 21142928 | doi = 10.1375/twin.13.6.517 | s2cid = 15730955 | doi-access = free }} 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.{{cite journal | vauthors = Wray NR, Lee SH, Mehta D, Vinkhuyzen AA, Dudbridge F, Middeldorp CM | title = Research review: Polygenic methods and their application to psychiatric traits | journal = Journal of Child Psychology and Psychiatry, and Allied Disciplines | volume = 55 | issue = 10 | pages = 1068–87 | year = 2014 | pmid = 25132410 | doi = 10.1111/jcpp.12295 | url = http://espace.library.uq.edu.au/view/UQ:342517/UQ342517_OA.pdf | access-date = 2019-07-01 | archive-date = 2017-01-16 | archive-url = https://web.archive.org/web/20170116084358/http://espace.library.uq.edu.au/view/UQ:342517/UQ342517_OA.pdf | url-status = live }}

Some behavioural genetic designs are useful not to understand genetic influences on behaviour, but to control for genetic influences to test environmentally-mediated influences on behaviour.{{cite journal | vauthors = McGue M, Osler M, Christensen K | title = Causal Inference and Observational Research: The Utility of Twins | journal = Perspectives on Psychological Science | volume = 5 | issue = 5 | pages = 546–56 | date = September 2010 | pmid = 21593989 | pmc = 3094752 | doi = 10.1177/1745691610383511 }} Such behavioural genetic designs may be considered a subset of natural experiments,{{cite journal | vauthors = Rutter M | title = Proceeding From Observed Correlation to Causal Inference: The Use of Natural Experiments | journal = Perspectives on Psychological Science | volume = 2 | issue = 4 | pages = 377–95 | date = December 2007 | pmid = 26151974 | doi = 10.1111/j.1745-6916.2007.00050.x | citeseerx = 10.1.1.649.2804 | s2cid = 205908149 }} 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.{{cite journal | vauthors = Kendler KS, Baker JH | title = Genetic influences on measures of the environment: a systematic review | journal = Psychological Medicine | volume = 37 | issue = 5 | pages = 615–26 | date = May 2007 | pmid = 17176502 | doi = 10.1017/S0033291706009524 | doi-broken-date = 1 November 2024 | s2cid = 43598144 }} 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 behavioural 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,{{cite journal | vauthors = Keyes M, Legrand LN, Iacono WG, McGue M | title = Parental smoking and adolescent problem behavior: an adoption study of general and specific effects | journal = The American Journal of Psychiatry | volume = 165 | issue = 10 | pages = 1338–44 | date = October 2008 | pmid = 18676589 | pmc = 2597022 | doi = 10.1176/appi.ajp.2008.08010125 }} {{non-primary source needed|date=February 2024}} but a larger effect of rearing environment on harder drug use.{{cite journal | vauthors = Kendler KS, Sundquist K, Ohlsson H, Palmér K, Maes H, Winkleby MA, Sundquist J | title = Genetic and familial environmental influences on the risk for drug abuse: a national Swedish adoption study | journal = Archives of General Psychiatry | volume = 69 | issue = 7 | pages = 690–7 | date = July 2012 | pmid = 22393206 | pmc = 3556483 | doi = 10.1001/archgenpsychiatry.2011.2112 }}{{non-primary source needed|date=February 2024}}

Other behavioural genetic designs include discordant twin studies, children of twins designs,{{cite journal | vauthors = D'Onofrio BM, Turkheimer EN, Eaves LJ, Corey LA, Berg K, Solaas MH, Emery RE | title = The role of the children of twins design in elucidating causal relations between parent characteristics and child outcomes | journal = Journal of Child Psychology and Psychiatry, and Allied Disciplines | volume = 44 | issue = 8 | pages = 1130–44 | date = November 2003 | pmid = 14626455 | doi = 10.1111/1469-7610.00196 }} and Mendelian randomization.{{cite journal | vauthors = Smith GD, Ebrahim S | title = Mendelian randomization: prospects, potentials, and limitations | journal = International Journal of Epidemiology | volume = 33 | issue = 1 | pages = 30–42 | date = February 2004 | pmid = 15075143 | doi = 10.1093/ije/dyh132 | doi-access = free }}

There are many broad conclusions to be drawn from behavioural genetic research about the nature and origins of behaviour.{{cite journal | vauthors = Plomin R, DeFries JC, Knopik VS, Neiderhiser JM | title = Top 10 Replicated Findings From Behavioral Genetics | journal = Perspectives on Psychological Science | volume = 11 | issue = 1 | pages = 3–23 | date = January 2016 | pmid = 26817721 | pmc = 4739500 | doi = 10.1177/1745691615617439 | publication-date = 27 January 2016 | author-link4 = Jenae Neiderhiser | author-link2 = John C. DeFries | author-link1 = Robert Plomin }} Three major conclusions include:

1. all behavioural traits and disorders are influenced by genes
2. environmental influences tend to make members of the same family more different, rather than more similar
3. the influence of genes tends to increase in relative importance as individuals age.

It is clear from multiple lines of evidence that all researched behavioural traits and disorders are influenced by genes; that is, they are heritable. The single largest source of evidence comes from twin studies, where it is routinely observed that monozygotic (identical) twins are more similar to one another than are same-sex dizygotic (fraternal) twins.

The conclusion that genetic influences are pervasive has also been observed in research designs that do not depend on the assumptions of the twin method. Adoption studies show that adoptees are routinely more similar to their biological relatives than their adoptive relatives for a wide variety of traits and disorders. In the Minnesota Study of Twins Reared Apart, monozygotic twins separated shortly after birth were reunited in adulthood.{{cite journal | vauthors = Bouchard TJ, Lykken DT, McGue M, Segal NL, Tellegen A | title = Sources of human psychological differences: the Minnesota Study of Twins Reared Apart | journal = Science | volume = 250 | issue = 4978 | pages = 223–8 | date = October 1990 | pmid = 2218526 | doi = 10.1126/science.2218526 | bibcode = 1990Sci...250..223B | citeseerx = 10.1.1.225.1769 | s2cid = 11794689 }} These adopted, reared-apart twins were as similar to one another as were twins reared together on a wide range of measures including general cognitive ability, personality, religious attitudes, and vocational interests, among others. Approaches using genome-wide genotyping have allowed researchers to measure genetic relatedness between individuals and estimate heritability based on millions of genetic variants. Methods exist to test whether the extent of genetic similarity (aka, relatedness) between nominally unrelated individuals (individuals who are not close or even distant relatives) is associated with phenotypic similarity.{{cite journal | vauthors = Yang J, Lee SH, Goddard ME, Visscher PM | title = GCTA: a tool for genome-wide complex trait analysis | journal = American Journal of Human Genetics | volume = 88 | issue = 1 | pages = 76–82 | date = January 2011 | pmid = 21167468 | pmc = 3014363 | doi = 10.1016/j.ajhg.2010.11.011 }} Such methods do not rely on the same assumptions as twin or adoption studies, and routinely find evidence for heritability of behavioural traits and disorders.{{cite journal | vauthors = Plomin R, Haworth CM, Meaburn EL, Price TS, Davis OS | title = Common DNA markers can account for more than half of the genetic influence on cognitive abilities | journal = Psychological Science | volume = 24 | issue = 4 | pages = 562–8 | date = April 2013 | pmid = 23501967 | pmc = 3652710 | doi = 10.1177/0956797612457952 }}

Just as all researched human behavioural phenotypes are influenced by genes (i.e., are heritable), all such phenotypes are also influenced by the environment.{{cite journal | vauthors = Polderman TJ, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A, Visscher PM, Posthuma D | title = Meta-analysis of the heritability of human traits based on fifty years of twin studies | journal = Nature Genetics | volume = 47 | issue = 7 | pages = 702–9 | date = July 2015 | pmid = 25985137 | doi = 10.1038/ng.3285 | s2cid = 205349969 | url = http://espace.library.uq.edu.au/view/UQ:364460/UQ364460_OA.pdf | access-date = 2019-01-30 | archive-date = 2022-04-20 | archive-url = https://web.archive.org/web/20220420013037/https://espace.library.uq.edu.au/data/UQ_364460/UQ364460_OA.pdf?Expires=1650418323&Key-Pair-Id=APKAJKNBJ4MJBJNC6NLQ&Signature=eO-xYmabg~9wp6eZ-kEj8RLKBtexGPSktde76DFFYxDCo3i~eZqiuDsd~VhC4iSnTeEkUqyWjVlng9b9-L-4XSmufnUWtBcksBNQDcRJKrk6CzejE~cqyLAp3SF~ZKAriWQ6TlEllv7gRcioSnW49Uf95yLKbHU9gQtjMMl1C0xKhOvSHOFuWX7c1POSKYNSdu1c1LVQQ1ZYuv1qUFw9Im8zGOe68MkDvVvEr9C5-w9LsrKFFy-f-9ZrA0CcRo9JZenudnMH9JeVdU8fv77x1gX52GidmRt6whwy1yMuE8KOfZNvs9-5YpxQCflxH95oezgiWi2QzwHchbS4U9lfzQ__ | url-status = live }} The basic fact that monozygotic twins are genetically identical but are never perfectly concordant for psychiatric disorder or perfectly correlated for behavioural traits, indicates that the environment shapes human behaviour.

The nature of this environmental influence, however, is such that it tends to make individuals in the same family more different from one another, not more similar to one another. That is, estimates of shared environmental effects ($c^2$) in human studies are small, negligible, or zero for the vast majority of behavioural traits and psychiatric disorders, whereas estimates of non-shared environmental effects ($e^2$) are moderate to large. From twin studies $c^2$ is typically estimated at 0 because the correlation ($r\_\{MZ\}$) between monozygotic twins is at least twice the correlation ($r\_\{DZ\}$) for dizygotic twins. When using the Falconer variance decomposition ($1.0\; =\; a^2\; +\; c^2\; +\; e^2$) this difference between monozygotic and dizygotic twin similarity results in an estimated $c^2=0$. The Falconer decomposition is simplistic. It removes the possible influence of dominance and epistatic effects which, if present, will tend to make monozygotic twins more similar than dizygotic twins and mask the influence of shared environmental effects. This is a limitation of the twin design for estimating $c^2$. However, the general conclusion that shared environmental effects are negligible does not rest on twin studies alone. Adoption research also fails to find large ($c^2$) components; that is, adoptive parents and their adopted children tend to show much less resemblance to one another than the adopted child and his or her non-rearing biological parent. In studies of adoptive families with at least one biological child and one adopted child, the sibling resemblance also tends to be nearly zero for most traits that have been studied.{{cite journal | vauthors = Plomin R, Daniels D | title = Why are children in the same family so different from one another? | journal = International Journal of Epidemiology | volume = 40 | issue = 3 | pages = 563–82 | date = June 2011 | pmid = 21807642 | pmc = 3147063 | doi = 10.1093/ije/dyq148 }}

File:Behavioral Genetics Twin Adoption Personality Similarity.pdf.]]

The figure provides an example from personality research, where twin and adoption studies converge on the conclusion of zero to small influences of shared environment on broad personality traits measured by the Multidimensional Personality Questionnaire including positive emotionality, negative emotionality, and constraint.{{cite journal | vauthors = Matteson LK, McGue M, Iacono WG | title = Shared environmental influences on personality: a combined twin and adoption approach | journal = Behavior Genetics | volume = 43 | issue = 6 | pages = 491–504 | date = November 2013 | pmid = 24065564 | pmc = 3868213 | doi = 10.1007/s10519-013-9616-8 }}

Given the conclusion that all researched behavioural traits and psychiatric disorders are heritable, biological siblings will always tend to be more similar to one another than will adopted siblings. However, for some traits, especially when measured during adolescence, adopted siblings do show some significant similarity (e.g., correlations of .20) to one another. Traits that have been demonstrated to have significant shared environmental influences include internalizing and externalizing psychopathology,{{cite journal | vauthors = Burt SA | title = Rethinking environmental contributions to child and adolescent psychopathology: a meta-analysis of shared environmental influences | journal = Psychological Bulletin | volume = 135 | issue = 4 | pages = 608–37 | date = July 2009 | pmid = 19586164 | doi = 10.1037/a0015702 }} substance use {{non-primary source needed|date=February 2024}} and dependence,{{non-primary source needed|date=February 2024}} and intelligence.{{cite journal | vauthors = Buchanan JP, McGue M, Keyes M, Iacono WG | title = Are there shared environmental influences on adolescent behavior? Evidence from a study of adoptive siblings | journal = Behavior Genetics | volume = 39 | issue = 5 | pages = 532–40 | date = September 2009 | pmid = 19626434 | pmc = 2858574 | doi = 10.1007/s10519-009-9283-y }} {{non-primary source needed|date=February 2024}}

Genetic effects on human behavioural outcomes can be described in multiple ways. One way to describe the effect is in terms of how much variance in the behaviour can be accounted for by alleles in the genetic variant, otherwise known as the coefficient of determination or $R^2$. An intuitive way to think about $R^2$ is that it describes the extent to which the genetic variant makes individuals, who harbour different alleles, different from one another on the behavioural outcome. A complementary way to describe effects of individual genetic variants is in how much change one expects on the behavioural outcome given a change in the number of risk alleles an individual harbours, often denoted by the Greek letter $\backslash beta$ (denoting the slope in a regression equation), or, in the case of binary disease outcomes by the odds ratio $OR$ of disease given allele status. Note the difference: $R^2$ describes the population-level effect of alleles within a genetic variant; $\backslash beta$ or $OR$ describe the effect of having a risk allele on the individual who harbours it, relative to an individual who does not harbour a risk allele.{{cite journal | vauthors = Bland JM, Altman DG | title = Statistics notes. The odds ratio | journal = BMJ | volume = 320 | issue = 7247 | pages = 1468 | date = May 2000 | pmid = 10827061 | pmc = 1127651 | doi = 10.1136/bmj.320.7247.1468 }}

When described on the $R^2$ metric, the effects of individual genetic variants on complex human behavioural traits and disorders are vanishingly small, with each variant accounting for of variation in the phenotype. This fact has been discovered primarily through genome-wide association studies of complex behavioural phenotypes, including results on substance use, personality, fertility,{{cite journal | vauthors = Day FR, Helgason H, Chasman DI, Rose LM, Loh PR, Scott RA, Helgason A, Kong A, Masson G, Magnusson OT, Gudbjartsson D, Thorsteinsdottir U, Buring JE, Ridker PM, Sulem P, Stefansson K, Ong KK, Perry JR | title = Physical and neurobehavioral determinants of reproductive onset and success | journal = Nature Genetics | volume = 48 | issue = 6 | pages = 617–23 | date = June 2016 | pmid = 27089180 | doi = 10.1038/ng.3551 | pmc = 5238953 }} schizophrenia, depression,{{cite journal | vauthors = ((CONVERGE consortium)) | title = Sparse whole-genome sequencing identifies two loci for major depressive disorder | journal = Nature | volume = 523 | issue = 7562 | pages = 588–91 | date = July 2015 | pmid = 26176920 | pmc = 4522619 | doi = 10.1038/nature14659 | bibcode = 2015Natur.523..588C }} and endophenotypes including brain structure and function.{{cite journal | vauthors = Iacono WG, Vaidyanathan U, Vrieze SI, Malone SM | title = Knowns and unknowns for psychophysiological endophenotypes: integration and response to commentaries | journal = Psychophysiology | volume = 51 | issue = 12 | pages = 1339–47 | date = December 2014 | pmid = 25387720 | pmc = 4231488 | doi = 10.1111/psyp.12358 }} There are a small handful of replicated and robustly studied exceptions to this rule, including the effect of APOE on Alzheimer's disease,{{cite journal | vauthors = Corder EH, Saunders AM, Risch NJ, Strittmatter WJ, Schmechel DE, Gaskell PC, Rimmler JB, Locke PA, Conneally PM, Schmader KE | title = Protective effect of apolipoprotein E type 2 allele for late onset Alzheimer disease | journal = Nature Genetics | volume = 7 | issue = 2 | pages = 180–4 | date = June 1994 | pmid = 7920638 | doi = 10.1038/ng0694-180 | s2cid = 11137478 }} and CHRNA5 on smoking behaviour, and ALDH2 (in individuals of East Asian ancestry) on alcohol use.{{cite journal | vauthors = Luczak SE, Glatt SJ, Wall TL | title = Meta-analyses of ALDH2 and ADH1B with alcohol dependence in Asians | journal = Psychological Bulletin | volume = 132 | issue = 4 | pages = 607–21 | date = July 2006 | pmid = 16822169 | doi = 10.1037/0033-2909.132.4.607 }}

On the other hand, when assessing effects according to the $\backslash beta$ metric, there are a large number of genetic variants that have very large effects on complex behavioural phenotypes. The risk alleles within such variants are exceedingly rare, such that their large behavioural effects impact only a small number of individuals. Thus, when assessed at a population level using the $R^2$ metric, they account for only a small amount of the differences in risk between individuals in the population. Examples include variants within APP that result in familial forms of severe early onset Alzheimer's disease but affect only relatively few individuals. Compare this to risk alleles within APOE, which pose much smaller risk compared to APP, but are far more common and therefore affect a much greater proportion of the population.{{cite journal | vauthors = Guerreiro RJ, Gustafson DR, Hardy J | title = The genetic architecture of Alzheimer's disease: beyond APP, PSENs and APOE | journal = Neurobiology of Aging | volume = 33 | issue = 3 | pages = 437–56 | date = March 2012 | pmid = 20594621 | pmc = 2980860 | doi = 10.1016/j.neurobiolaging.2010.03.025 }}

Finally, there are classical behavioural disorders that are genetically simple in their etiology, such as Huntington's disease. Huntington's is caused by a single autosomal dominant variant in the HTT gene, which is the only variant that accounts for any differences among individuals in their risk for developing the disease, assuming they live long enough.{{cite journal | vauthors = Gusella JF, Wexler NS, Conneally PM, Naylor SL, Anderson MA, Tanzi RE, Watkins PC, Ottina K, Wallace MR, Sakaguchi AY | title = A polymorphic DNA marker genetically linked to Huntington's disease | journal = Nature | volume = 306 | issue = 5940 | pages = 234–8 | year = 1983 | pmid = 6316146 | doi = 10.1038/306234a0 | bibcode = 1983Natur.306..234G | s2cid = 4320711 }} In the case of genetically simple and rare diseases such as Huntington's, the variant $R^2$ and the $OR$ are simultaneously large.

In response to general concerns about the replicability of psychological research, behavioural geneticists Robert Plomin, John C. DeFries, Valerie Knopik, and Jenae Neiderhiser published a review of the ten most well-replicated findings from behavioural genetics research. The ten findings were:

1. "All psychological traits show significant and substantial genetic influence."
2. "No behavioural traits are 100% heritable."
3. "Heritability is caused by many genes of small effect."
4. "Phenotypic correlations between psychological traits show significant and substantial genetic mediation."
5. "The heritability of intelligence increases throughout development."
6. "Age-to-age stability is mainly due to genetics."
7. "Most measures of the 'environment' show significant genetic influence."
8. "Most associations between environmental measures and psychological traits are significantly mediated genetically."
9. "Most environmental effects are not shared by children growing up in the same family."
10. "Abnormal is normal."

{{See also|Missing heritability problem}}

Behavioural genetic research and findings have at times been controversial. Some of this controversy has arisen because behavioural genetic findings can challenge societal beliefs about the nature of human behaviour and abilities. Major areas of controversy have included genetic research on topics such as racial differences, intelligence, violence, and human sexuality.{{cite journal | vauthors = Hayden EC | title = Ethics: Taboo genetics | journal = Nature | volume = 502 | issue = 7469 | pages = 26–8 | date = October 2013 | pmid = 24091964 | doi = 10.1038/502026a | bibcode = 2013Natur.502...26C | doi-access = free }} Other controversies have arisen due to misunderstandings of behavioural genetic research, whether by the lay public or the researchers themselves. For example, the notion of heritability is easily misunderstood to imply causality, or that some behaviour or condition is determined by one's genetic endowment. When behavioural genetics researchers say that a behaviour is X% heritable, that does not mean that genetics causes, determines, or fixes up to X% of the behaviour. Instead, heritability is a statement about genetic differences correlated with trait differences on the population level.{{Citation needed|date=June 2020}}

Historically, perhaps the most controversial subject has been on race and genetics. Race is not a scientifically exact term, and its interpretation can depend on one's culture and country of origin.{{cite journal | vauthors = Yudell M, Roberts D, DeSalle R, Tishkoff S | title = Science and Society: Taking race out of human genetics | journal = Science | volume = 351 | issue = 6273 | pages = 564–5 | date = February 2016 | pmid = 26912690 | doi = 10.1126/science.aac4951 | bibcode = 2016Sci...351..564Y | s2cid = 206639306 }} Instead, geneticists use concepts such as ancestry, which is more rigorously defined.{{cite journal | vauthors = Bryc K, Durand EY, Macpherson JM, Reich D, Mountain JL | title = The genetic ancestry of African Americans, Latinos, and European Americans across the United States | journal = American Journal of Human Genetics | volume = 96 | issue = 1 | pages = 37–53 | date = January 2015 | pmid = 25529636 | pmc = 4289685 | doi = 10.1016/j.ajhg.2014.11.010 }} For example, a so-called "Black" race may include all individuals of relatively recent African descent ("recent" because all humans are descended from African ancestors). However, there is more genetic diversity in Africa than the rest of the world combined,{{cite journal | vauthors = Abecasis GR, Auton A, Brooks LD, DePristo MA, Durbin RM, Handsaker RE, Kang HM, Marth GT, McVean GA | title = An integrated map of genetic variation from 1,092 human genomes | journal = Nature | volume = 491 | issue = 7422 | pages = 56–65| date = November 2012 | pmid = 23128226 | pmc = 3498066 | doi = 10.1038/nature11632 | bibcode = 2012Natur.491...56T }} so speaking of a "Black" race is without a precise genetic meaning.

Qualitative research has fostered arguments that behavioural genetics is an ungovernable field without scientific norms or consensus, which fosters controversy. The argument continues that this state of affairs has led to controversies including race, intelligence, instances where variation within a single gene was found to very strongly influence a controversial phenotype (e.g., the "gay gene" controversy), and others. This argument further states that because of the persistence of controversy in behaviour genetics and the failure of disputes to be resolved, behaviour genetics does not conform to the standards of good science.{{cite book| vauthors = Panofsky A |title=Misbehaving Science: Controversy and the Development of Behavior Genetics|url=https://books.google.com/books?id=9bHBAwAAQBAJ|date=7 July 2014|publisher=University of Chicago Press|isbn=978-0-226-05859-7|access-date=23 May 2018|archive-date=22 April 2021|archive-url= https://web.archive.org/web/20210422233432/https://books.google.com/books?id=9bHBAwAAQBAJ|url-status=live}}

The scientific assumptions on which parts of behavioural genetic research are based have also been criticized as flawed.{{cite journal | vauthors = Charney E | title = Genes, behavior, and behavior genetics | journal = Wiley Interdisciplinary Reviews: Cognitive Science | volume = 8 | issue = 1–2 | pages = e1405 | date = January 2017 | pmid = 27906529 | doi = 10.1002/wcs.1405 | hdl = 10161/13337 | hdl-access = free }} Genome wide association studies are often implemented with simplifying statistical assumptions, such as additivity, which may be statistically robust but unrealistic for some behaviours. Critics further contend that, in humans, behaviour genetics represents a misguided form of genetic reductionism based on inaccurate interpretations of statistical analyses.{{Cite journal |vauthors = Lerner RM |date=27 August 2015 |title=Eliminating Genetic Reductionism from Developmental Science |journal=Research in Human Development |volume=12 |issue=3–4 |pages=178–188 |doi=10.1080/15427609.2015.1068058 |s2cid=143195504 |issn=1542-7609|doi-access=free }} Studies comparing monozygotic (MZ) and dizygotic (DZ) twins assume that environmental influences will be the same in both types of twins, but this assumption may also be unrealistic. MZ twins may be treated more alike than DZ twins, which itself may be an example of evocative gene–environment correlation, suggesting that one's genes influence their treatment by others. It is also not possible in twin studies to eliminate effects of the shared womb environment, although studies comparing twins who experience monochorionic and dichorionic environments in utero do exist, and indicate limited impact.{{cite journal | vauthors = van Beijsterveldt CE, Overbeek LI, Rozendaal L, McMaster MT, Glasner TJ, Bartels M, Vink JM, Martin NG, Dolan CV, Boomsma DI | title = Chorionicity and Heritability Estimates from Twin Studies: The Prenatal Environment of Twins and Their Resemblance Across a Large Number of Traits | journal = Behavior Genetics | volume = 46 | issue = 3 | pages = 304–14 | date = May 2016 | pmid = 26410687 | doi = 10.1007/s10519-015-9745-3 | pmc = 4858554 }} Studies of twins separated in early life include children who were separated not at birth but part way through childhood. The effect of early rearing environment can therefore be evaluated to some extent in such a study, by comparing twin similarity for those twins separated early and those separated later.

{{Div col|colwidth=30em}}

• Behavior Genetics
• Behavior Genetics Association
• Behavioural neurogenetics
• Biocultural evolution
• Evolutionary psychology
• Genes, Brain and Behavior
• Genome-wide association study
• International Behavioural and Neural Genetics Society
• International Society of Psychiatric Genetics
• Journal of Neurogenetics
• Nature versus nurture
• Personality psychology
• Psychiatric genetics
• Psychiatric Genetics
• Quantitative genetics
• Tryon's Rat Experiment

{{div col end}}

{{reflist|30em|refs =

{{cite journal | vauthors = Duncan LE, Keller MC | title = A critical review of the first 10 years of candidate gene-by-environment interaction research in psychiatry | journal = The American Journal of Psychiatry | volume = 168 | issue = 10 | pages = 1041–9 | date = October 2011 | pmid = 21890791 | pmc = 3222234 | doi = 10.1176/appi.ajp.2011.11020191 }}

{{cite journal | vauthors = de Moor MH, van den Berg SM, Verweij KJ, Krueger RF, Luciano M, Arias Vasquez A, Matteson LK, Derringer J, Esko T, Amin N, Gordon SD, Hansell NK, Hart AB, Seppälä I, Huffman JE, Konte B, Lahti J, Lee M, Miller M, Nutile T, Tanaka T, Teumer A, Viktorin A, Wedenoja J, Abecasis GR, Adkins DE, Agrawal A, Allik J, Appel K, Bigdeli TB, Busonero F, Campbell H, Costa PT, Davey Smith G, Davies G, de Wit H, Ding J, Engelhardt BE, Eriksson JG, Fedko IO, Ferrucci L, Franke B, Giegling I, Grucza R, Hartmann AM, Heath AC, Heinonen K, Henders AK, Homuth G, Hottenga JJ, Iacono WG, Janzing J, Jokela M, Karlsson R, Kemp JP, Kirkpatrick MG, Latvala A, Lehtimäki T, Liewald DC, Madden PA, Magri C, Magnusson PK, Marten J, Maschio A, Medland SE, Mihailov E, Milaneschi Y, Montgomery GW, Nauck M, Ouwens KG, Palotie A, Pettersson E, Polasek O, Qian Y, Pulkki-Råback L, Raitakari OT, Realo A, Rose RJ, Ruggiero D, Schmidt CO, Slutske WS, Sorice R, Starr JM, St Pourcain B, Sutin AR, Timpson NJ, Trochet H, Vermeulen S, Vuoksimaa E, Widen E, Wouda J, Wright MJ, Zgaga L, Porteous D, Minelli A, Palmer AA, Rujescu D, Ciullo M, Hayward C, Rudan I, Metspalu A, Kaprio J, Deary IJ, Räikkönen K, Wilson JF, Keltikangas-Järvinen L, Bierut LJ, Hettema JM, Grabe HJ, van Duijn CM, Evans DM, Schlessinger D, Pedersen NL, Terracciano A, McGue M, Penninx BW, Martin NG, Boomsma DI | title = Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder | journal = JAMA Psychiatry | volume = 72 | issue = 7 | pages = 642–50 | date = July 2015 | pmid = 25993607 | pmc = 4667957 | doi = 10.1001/jamapsychiatry.2015.0554 }}

{{cite journal | vauthors = Hibar DP, Stein JL, Renteria ME, Arias-Vasquez A, Desrivières S, Jahanshad N, Toro R, Wittfeld K, Abramovic L, Andersson M, Aribisala BS, Armstrong NJ, Bernard M, Bohlken MM, Boks MP, Bralten J, Brown AA, Chakravarty MM, Chen Q, Ching CR, Cuellar-Partida G, den Braber A, Giddaluru S, Goldman AL, Grimm O, Guadalupe T, Hass J, Woldehawariat G, Holmes AJ, Hoogman M, Janowitz D, Jia T, Kim S, Klein M, Kraemer B, Lee PH, Olde Loohuis LM, Luciano M, Macare C, Mather KA, Mattheisen M, Milaneschi Y, Nho K, Papmeyer M, Ramasamy A, Risacher SL, Roiz-Santiañez R, Rose EJ, Salami A, Sämann PG, Schmaal L, Schork AJ, Shin J, Strike LT, Teumer A, van Donkelaar MM, van Eijk KR, Walters RK, Westlye LT, Whelan CD, Winkler AM, Zwiers MP, Alhusaini S, Athanasiu L, Ehrlich S, Hakobjan MM, Hartberg CB, Haukvik UK, Heister AJ, Hoehn D, Kasperaviciute D, Liewald DC, Lopez LM, Makkinje RR, Matarin M, Naber MA, McKay DR, Needham M, Nugent AC, Pütz B, Royle NA, Shen L, Sprooten E, Trabzuni D, van der Marel SS, van Hulzen KJ, Walton E, Wolf C, Almasy L, Ames D, Arepalli S, Assareh AA, Bastin ME, Brodaty H, Bulayeva KB, Carless MA, Cichon S, Corvin A, Curran JE, Czisch M, de Zubicaray GI, Dillman A, Duggirala R, Dyer TD, Erk S, Fedko IO, Ferrucci L, Foroud TM, Fox PT, Fukunaga M, Gibbs JR, Göring HH, Green RC, Guelfi S, Hansell NK, Hartman CA, Hegenscheid K, Heinz A, Hernandez DG, Heslenfeld DJ, Hoekstra PJ, Holsboer F, Homuth G, Hottenga JJ, Ikeda M, Jack CR, Jenkinson M, Johnson R, Kanai R, Keil M, Kent JW, Kochunov P, Kwok JB, Lawrie SM, Liu X, Longo DL, McMahon KL, Meisenzahl E, Melle I, Mohnke S, Montgomery GW, Mostert JC, Mühleisen TW, Nalls MA, Nichols TE, Nilsson LG, Nöthen MM, Ohi K, Olvera RL, Perez-Iglesias R, Pike GB, Potkin SG, Reinvang I, Reppermund S, Rietschel M, Romanczuk-Seiferth N, Rosen GD, Rujescu D, Schnell K, Schofield PR, Smith C, Steen VM, Sussmann JE, Thalamuthu A, Toga AW, Traynor BJ, Troncoso J, Turner JA, Valdés Hernández MC, van 't Ent D, van der Brug M, van der Wee NJ, van Tol MJ, Veltman DJ, Wassink TH, Westman E, Zielke RH, Zonderman AB, Ashbrook DG, Hager R, Lu L, McMahon FJ, Morris DW, Williams RW, Brunner HG, Buckner RL, Buitelaar JK, Cahn W, Calhoun VD, Cavalleri GL, Crespo-Facorro B, Dale AM, Davies GE, Delanty N, Depondt C, Djurovic S, Drevets WC, Espeseth T, Gollub RL, Ho BC, Hoffmann W, Hosten N, Kahn RS, Le Hellard S, Meyer-Lindenberg A, Müller-Myhsok B, Nauck M, Nyberg L, Pandolfo M, Penninx BW, Roffman JL, Sisodiya SM, Smoller JW, van Bokhoven H, van Haren NE, Völzke H, Walter H, Weiner MW, Wen W, White T, Agartz I, Andreassen OA, Blangero J, Boomsma DI, Brouwer RM, Cannon DM, Cookson MR, de Geus EJ, Deary IJ, Donohoe G, Fernández G, Fisher SE, Francks C, Glahn DC, Grabe HJ, Gruber O, Hardy J, Hashimoto R, Hulshoff Pol HE, Jönsson EG, Kloszewska I, Lovestone S, Mattay VS, Mecocci P, McDonald C, McIntosh AM, Ophoff RA, Paus T, Pausova Z, Ryten M, Sachdev PS, Saykin AJ, Simmons A, Singleton A, Soininen H, Wardlaw JM, Weale ME, Weinberger DR, Adams HH, Launer LJ, Seiler S, Schmidt R, Chauhan G, Satizabal CL, Becker JT, Yanek L, van der Lee SJ, Ebling M, Fischl B, Longstreth WT, Greve D, Schmidt H, Nyquist P, Vinke LN, van Duijn CM, Xue L, Mazoyer B, Bis JC, Gudnason V, Seshadri S, Ikram MA, Martin NG, Wright MJ, Schumann G, Franke B, Thompson PM, Medland SE | title = Common genetic variants influence human subcortical brain structures | journal = Nature | volume = 520 | issue = 7546 | pages = 224–9 | date = April 2015 | pmid = 25607358 | pmc = 4393366 | doi = 10.1038/nature14101 | bibcode = 2015Natur.520..224. }}

{{cite journal | vauthors = Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, Meddens SF, Linnér RK, Rietveld CA, Derringer J, Gratten J, Lee JJ, Liu JZ, de Vlaming R, Ahluwalia TS, Buchwald J, Cavadino A, Frazier-Wood AC, Furlotte NA, Garfield V, Geisel MH, Gonzalez JR, Haitjema S, Karlsson R, van der Laan SW, Ladwig KH, Lahti J, van der Lee SJ, Lind PA, Liu T, Matteson L, Mihailov E, Miller MB, Minica CC, Nolte IM, Mook-Kanamori D, van der Most PJ, Oldmeadow C, Qian Y, Raitakari O, Rawal R, Realo A, Rueedi R, Schmidt B, Smith AV, Stergiakouli E, Tanaka T, Taylor K, Wedenoja J, Wellmann J, Westra HJ, Willems SM, Zhao W, Amin N, Bakshi A, Boyle PA, Cherney S, Cox SR, Davies G, Davis OS, Ding J, Direk N, Eibich P, Emeny RT, Fatemifar G, Faul JD, Ferrucci L, Forstner A, Gieger C, Gupta R, Harris TB, Harris JM, Holliday EG, Hottenga JJ, De Jager PL, Kaakinen MA, Kajantie E, Karhunen V, Kolcic I, Kumari M, Launer LJ, Franke L, Li-Gao R, Koini M, Loukola A, Marques-Vidal P, Montgomery GW, Mosing MA, Paternoster L, Pattie A, Petrovic KE, Pulkki-Råback L, Quaye L, Räikkönen K, Rudan I, Scott RJ, Smith JA, Sutin AR, Trzaskowski M, Vinkhuyzen AE, Yu L, Zabaneh D, Attia JR, Bennett DA, Berger K, Bertram L, Boomsma DI, Snieder H, Chang SC, Cucca F, Deary IJ, van Duijn CM, Eriksson JG, Bültmann U, de Geus EJ, Groenen PJ, Gudnason V, Hansen T, Hartman CA, Haworth CM, Hayward C, Heath AC, Hinds DA, Hyppönen E, Iacono WG, Järvelin MR, Jöckel KH, Kaprio J, Kardia SL, Keltikangas-Järvinen L, Kraft P, Kubzansky LD, Lehtimäki T, Magnusson PK, Martin NG, McGue M, Metspalu A, Mills M, de Mutsert R, Oldehinkel AJ, Pasterkamp G, Pedersen NL, Plomin R, Polasek O, Power C, Rich SS, Rosendaal FR, den Ruijter HM, Schlessinger D, Schmidt H, Svento R, Schmidt R, Alizadeh BZ, Sørensen TI, Spector TD, Steptoe A, Terracciano A, Thurik AR, Timpson NJ, Tiemeier H, Uitterlinden AG, Vollenweider P, Wagner GG, Weir DR, Yang J, Conley DC, Smith GD, Hofman A, Johannesson M, Laibson DI, Medland SE, Meyer MN, Pickrell JK, Esko T, Krueger RF, Beauchamp JP, Koellinger PD, Benjamin DJ, Bartels M, Cesarini D | title = Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses | journal = Nature Genetics | volume = 48 | issue = 6 | pages = 624–33 | date = June 2016 | pmid = 27089181 | pmc = 4884152 | doi = 10.1038/ng.3552 }}

{{cite journal | vauthors = Schumann G, Coin LJ, Lourdusamy A, Charoen P, Berger KH, Stacey D, Desrivières S, Aliev FA, Khan AA, Amin N, Aulchenko YS, Bakalkin G, Bakker SJ, Balkau B, Beulens JW, Bilbao A, de Boer RA, Beury D, Bots ML, Breetvelt EJ, Cauchi S, Cavalcanti-Proença C, Chambers JC, Clarke TK, Dahmen N, de Geus EJ, Dick D, Ducci F, Easton A, Edenberg HJ, Esko T, Esk T, Fernández-Medarde A, Foroud T, Freimer NB, Girault JA, Grobbee DE, Guarrera S, Gudbjartsson DF, Hartikainen AL, Heath AC, Hesselbrock V, Hofman A, Hottenga JJ, Isohanni MK, Kaprio J, Khaw KT, Kuehnel B, Laitinen J, Lobbens S, Luan J, Mangino M, Maroteaux M, Matullo G, McCarthy MI, Mueller C, Navis G, Numans ME, Núñez A, Nyholt DR, Onland-Moret CN, Oostra BA, O'Reilly PF, Palkovits M, Penninx BW, Polidoro S, Pouta A, Prokopenko I, Ricceri F, Santos E, Smit JH, Soranzo N, Song K, Sovio U, Stumvoll M, Surakk I, Thorgeirsson TE, Thorsteinsdottir U, Troakes C, Tyrfingsson T, Tönjes A, Uiterwaal CS, Uitterlinden AG, van der Harst P, van der Schouw YT, Staehlin O, Vogelzangs N, Vollenweider P, Waeber G, Wareham NJ, Waterworth DM, Whitfield JB, Wichmann EH, Willemsen G, Witteman JC, Yuan X, Zhai G, Zhao JH, Zhang W, Martin NG, Metspalu A, Doering A, Scott J, Spector TD, Loos RJ, Boomsma DI, Mooser V, Peltonen L, Stefansson K, van Duijn CM, Vineis P, Sommer WH, Kooner JS, Spanagel R, Heberlein UA, Jarvelin MR, Elliott P | title = Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption | journal = Proceedings of the National Academy of Sciences of the United States of America | volume = 108 | issue = 17 | pages = 7119–24 | date = April 2011 | pmid = 21471458 | pmc = 3084048 | doi = 10.1073/pnas.1017288108 | bibcode = 2011PNAS..108.7119S | doi-access = free }}

{{cite journal | vauthors = Thorgeirsson TE, Gudbjartsson DF, Surakka I, Vink JM, Amin N, Geller F, Sulem P, Rafnar T, Esko T, Walter S, Gieger C, Rawal R, Mangino M, Prokopenko I, Mägi R, Keskitalo K, Gudjonsdottir IH, Gretarsdottir S, Stefansson H, Thompson JR, Aulchenko YS, Nelis M, Aben KK, den Heijer M, Dirksen A, Ashraf H, Soranzo N, Valdes AM, Steves C, Uitterlinden AG, Hofman A, Tönjes A, Kovacs P, Hottenga JJ, Willemsen G, Vogelzangs N, Döring A, Dahmen N, Nitz B, Pergadia ML, Saez B, De Diego V, Lezcano V, Garcia-Prats MD, Ripatti S, Perola M, Kettunen J, Hartikainen AL, Pouta A, Laitinen J, Isohanni M, Huei-Yi S, Allen M, Krestyaninova M, Hall AS, Jones GT, van Rij AM, Mueller T, Dieplinger B, Haltmayer M, Jonsson S, Matthiasson SE, Oskarsson H, Tyrfingsson T, Kiemeney LA, Mayordomo JI, Lindholt JS, Pedersen JH, Franklin WA, Wolf H, Montgomery GW, Heath AC, Martin NG, Madden PA, Giegling I, Rujescu D, Järvelin MR, Salomaa V, Stumvoll M, Spector TD, Wichmann HE, Metspalu A, Samani NJ, Penninx BW, Oostra BA, Boomsma DI, Tiemeier H, van Duijn CM, Kaprio J, Gulcher JR, McCarthy MI, Peltonen L, Thorsteinsdottir U, Stefansson K | title = Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior | journal = Nature Genetics | volume = 42 | issue = 5 | pages = 448–53 | date = May 2010 | pmid = 20418888 | pmc = 3080600 | doi = 10.1038/ng.573 }}

}}

{{refbegin|33em}}

• {{cite journal |doi=10.1016/j.cobeha.2014.10.002 |title=Key issues in contemporary behavioral genetics |journal=Current Opinion in Behavioral Sciences |volume=2 |pages=89–95 |year=2015 | vauthors = Crusio WE |s2cid=53200512 |author1-link=Wim Crusio }}
• {{cite book | veditors = Crusio WE, Gerlai RT |editor2-link=Robert Gerlai |title=Handbook of Molecular-Genetic Techniques for Brain and Behavior Research |isbn=978-0-444-50239-1 |series=Techniques in the Behavioral and Neural Sciences |volume=13 |date=1999 |publisher=Elsevier }}
• {{cite book | veditors = Crusio WE, Sluyter F, Gerlai RT, Pietropaolo S |editor3-link=Robert Gerlai |title=Behavioral Genetics of the Mouse: Genetics of Behavioral Phenotypes |volume=1 |series=Cambridge Handbooks in Behavioral Genetics |publisher=Cambridge University Press |date=2013 |isbn=978-1-107-03481-5 }}
• {{cite book | vauthors = Flint J, Greenspan RJ, Kendler KS |author-link3=Kenneth Kendler |title=How Genes Influence Behavior |url= https://archive.org/details/howgenesinfl_flin_2010_000_10540804 |url-access=registration |date=28 January 2010 |publisher=Oxford University Press |isbn=978-0-19-955990-9 }}
• {{cite journal | vauthors = Johnson W, Turkheimer E, Gottesman II, Bouchard TJ | title = Beyond Heritability: Twin Studies in Behavioral Research | journal = Current Directions in Psychological Science | volume = 18 | issue = 4 | pages = 217–220 | date = August 2010 | pmid = 20625474 | pmc = 2899491 | doi = 10.1111/j.1467-8721.2009.01639.x | author-link4 = Thomas J. Bouchard Jr. | author-link3 = Irving Gottesman }}
• {{cite journal | vauthors = Johnson W, Penke L, Spinath FM |title=Understanding Heritability: What it is and What it is Not |access-date=15 December 2013 |journal=European Journal of Personality |volume=25 |issue=4 |date=2011 |pages=287–294 |issn=0890-2070 |doi=10.1002/per.835 |s2cid=41842465 |url=http://www.larspenke.eu/pdfs/Johnson_Penke_Spinath_2011_-_Heritability_rejoinder.pdf |archive-date=16 December 2013 |url-status=live |archive-url=https://web.archive.org/web/20131216034914/http://www.larspenke.eu/pdfs/Johnson_Penke_Spinath_2011_-_Heritability_rejoinder.pdf }}
• {{cite book | vauthors = Maxson SC | veditors = Weiner IB, Nelson RJ, Mizumori S |title=Handbook of Psychology (Volume 3: Behavioral Neuroscience) |chapter-url= http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470890592.html |access-date=15 December 2013 |chapter=Chapter 1: Behavioral Genetics |date=10 October 2012 |publisher=John Wiley & Sons |isbn=978-0-470-89059-2 |archive-url=https://web.archive.org/web/20131216050019/http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470890592.html |archive-date=16 December 2013 |url-status=live }}
• {{cite book | vauthors = Spinath FM, Johnson W |title=The Wiley-Blackwell Handbook of Individual Differences | veditors = Chamorro-Premuzic T, von Stumm S, Furnham A |chapter= Chapter 10: Behavior Genetics |date=2011 |publisher=Blackwell Publishing Ltd |location=United Kingdom |isbn=978-1-4443-3438-8 |doi=10.1002/9781444343120 }}

{{refend}}

{{Commons category}}

• {{cite web |url=https://www.coursera.org/learn/behavioralgenetics |title=Introduction to Human Behavioral Genetics | vauthors = McGue M | author-link1 = Matt McGue |date=5 May 2014 |website=Coursera |access-date=10 June 2014}}
• {{cite web |url=https://sites.google.com/umn.edu/behavioralgenetics-mcgue/home-topics |title=Introduction to Behavioral Genetics | vauthors = McGue M | author-link1 = Matt McGue |date=December 2020 |website=University of Minnesota |access-date=28 June 2021}}
• {{cite web |url=https://bga.org/ |title=Behavior Genetics Association |website=Behavior Genetics Association|access-date=8 May 2022}}
• {{citation | url = http://www.colorado.edu/ibg/ | title = Institute for Behavioral Genetics at the University of Colorado Boulder | publisher = University of Colorado Boulder }}
• {{cite web | url = http://vipbg.vcu.edu/ | title = Virginia Institute for Psychiatric and Behavioral Genetics | publisher = Virginia Commonwealth University }}

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{{Neuroscience}}

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{{DEFAULTSORT:Behavioural Genetics}}