Intelligence is a core construct in differential psychology and behavioural genetics, and should be so in cognitive neuroscience. It is one of the best predictors of important life outcomes such as education, occupation, mental and physical health and illness, and mortality. Intelligence is one of the most heritable behavioural traits. Here, we highlight five genetic findings that are special to intelligence differences and that have important implications for its genetic architecture and for gene-hunting expeditions. (i) The heritability of intelligence increases from about 20% in infancy to perhaps 80% in later adulthood. (ii) Intelligence captures genetic effects on diverse cognitive and learning abilities, which correlate phenotypically about 0.30 on average but correlate genetically about 0.60 or higher. (iii) Assortative mating is greater for intelligence (spouse correlations ~0.40) than for other behavioural traits such as personality and psychopathology (~0.10) or physical traits such as height and weight (~0.20). Assortative mating pumps additive genetic variance into the population every generation, contributing to the high narrow heritability (additive genetic variance) of intelligence. (iv) Unlike psychiatric disorders, intelligence is normally distributed with a positive end of exceptional performance that is a model for ‘positive genetics'. (v) Intelligence is associated with education and social class and broadens the causal perspectives on how these three inter-correlated variables contribute to social mobility, and health, illness and mortality differences. These five findings arose primarily from twin studies. They are being confirmed by the first new quantitative genetic technique in a century—Genome-wide Complex Trait Analysis (GCTA)—which estimates genetic influence using genome-wide genotypes in large samples of unrelated individuals. Comparing GCTA results to the results of twin studies reveals important insights into the genetic architecture of intelligence that are relevant to attempts to narrow the ‘missing heritability' gap. We begin by noting three regularities that might almost be dubbed ‘laws' from genetic research that apply to many traits in the life sciences. The bulk of our review highlights genetic findings that are specific to intelligence rather than these general laws.7 Although the pervasiveness of this finding makes it a commonplace observation, it should not be taken for granted, especially in the behavioural sciences, because this was the battleground for nature-nurture wars until only a few decades ago in psychiatry,8 even fewer decades ago in psychology,9 and continuing today in some areas such as education.11 It might be argued that it is no longer surprising to demonstrate genetic influence on a behavioural trait, and that it would be more interesting to find a trait that shows no genetic influence.Finding that differences between individuals  are significantly heritable is so ubiquitous for behavioural traits that it has been enshrined as the first law of behavioural genetics.et al.For some areas of behavioural research—especially in psychiatry—the pendulum has swung so far from a focus on nurture to a focus on nature that it is important to highlight a second law of genetics for complex traits and common disorders: All traits show substantial environmental influence, in that heritability is not 100% for any trait. Acceptance of the importance of both genetic and environmental influences leads to interest in the interplay between genes and environment, such as their interaction (moderation) and correlation (mediation) in the development of complex traits, Plomin 12 This was the premise of quantitative genetic theory set out nearly a century ago,13 but quantitative genetic methods themselves could not shine much light on the distribution of the effect sizes of genes in the population. For decades, the failure of linkage analyses to identify replicable linkages to chromosomal regions could be interpreted as support for this hypothesis because linkage has little power to detect small effect sizes. However, GWA studies have made it clear that the largest effect sizes of associations are very small indeed. For example, we are aware of almost no replicated genetic associations that account for more than 1 per cent of the population variance of quantitative traits such as height and weight. Because GWA studies have adequate power to detect such effect sizes, we can conclude that there are no larger effect sizes, at least for the common single-nucleotide variants that have been used in such studies to date. If the largest effect sizes are so small, the smallest effect sizes must be infinitesimal, which means that such associations will be difficult to detect and even more difficult to replicate. For example, the largest GWA study of intelligence differences, which included nearly 18 000 children, found no genome-wide significant associations. The largest effect sizes accounted for 0.2% of the variance of intelligence scores.14 Another recent GWA study of a sample of 1500 children reported an association that accounted for 0.5% of the variance of intelligence scores,15 but this association showed no effect in the study of 18 000 children . A GWA of educational attainment—which correlates moderately with intelligence—included more than 125 000 individuals; the DNA variant with the largest effect size accounted for 1% of the variance in years of education but the variance explained was only 0.02% in a replication sample.16 ‘Missing heritability' is the catch-phrase to describe the great gulf between heritability and the variance explained by associations with specific DNA variants.The first two laws come from quantitative genetic research, which uses, for example, the twin method to assess the net contribution of genetics to individual differences without knowledge of the genetic architecture of a trait, such as the number of genes involved or their effect sizes. A third law has emerged from molecular genetic research that attempts to identify specific genes responsible for widespread heritability, especially genome-wide association (GWA) studies of the past few years: The heritability of traits is caused by many genes of small effect.11 we begin by briefly discussing the definition, measurement and importance of intelligence.Rather than reviewing evidence for these general laws in relation to intelligence, our review focuses on five findings from genetic research that are specific to intelligence. Because of the controversy and confusion that continues to surround intelligence, especially in the media and the general science literature,general cognitive ability or g, as discovered and defined by Spearman in 190417) indexes this covariance, which accounts for about 40 per cent of the total variance when a battery of diverse cognitive tests is administered to a sample with a good range of cognitive ability.19 As long as a battery of cognitive tests is diverse and reliable, a general ‘factor'  indexing intelligence differences will emerge and correlate highly with such factors derived from other batteries using wholly different cognitive tests.20 The general intelligence component (factor) is a universally found statistical regularity, which means that some have tried to provide an epithet for what it might capture. According to one view, the core of this general intelligence factor is ‘the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience' . Intelligence is at the pinnacle of the hierarchical model of cognitive abilities that includes a middle level of group factors, such as the cognitive domains of verbal and spatial abilities and memory, and a third level of specific tests and their associated narrow cognitive skills.23Although there are many types of cognitive ability tests of individual differences, they almost all correlate substantially and positively; people with higher ability on one cognitive task tend to have higher ability on all of the others. Intelligence ,35 is the first new human quantitative genetic method in a century, and is described in The rest of this review describes five genetic findings that are special to intelligence differences: dramatic increases in heritability during the life course, high genetic correlations among diverse cognitive abilities, high assortative mating, the positive genetics of high intelligence and the impact of intelligence on ‘social epidemiology'. Most of these findings are not new,47 but then decline to about 60% after age 80.48It would be reasonable to assume that as we go through life, experiences—Shakespeare's ‘whips and scorns of time'—have a cumulative effect on intelligence, perhaps overwhelming early genetic predispositions. However, for intelligence, heritability increases linearly, from (approximately) 20% in infancy to 40% in adolescence, and to 60% in adulthood. Some evidence suggests that heritability might increase to as much as 80% in later adulthood49 The non-overlapping standard errors across the three ages indicate that the increases in heritabilities are significant. Although these findings have been criticised because they rely on cross-sectional comparisons (Mackintosh50 p. 278), similar results showing increases in heritability have been found in longitudinal adoption studies52 as well as in longitudinal twin studies from early to middle childhood54 and from middle childhood to adolescence.55 Although GCTA can be used to test this finding of increasing heritability across development, the first two attempts to do so using longitudinal data did not have sufficient power to detect the hypothesised age differences in GCTA heritability. One study reported an increase in GCTA heritability of intelligence from 0.26 (0.17 standard error) at age 7 to 0.45 (0.14) at age 12.56 Another study reported a decrease in GCTA heritability from 0.48 (0.18) at age 11 to 0.28 (0.18) in old age.46 Given the differences in the ages tested in these latter two studies, they are not directly comparable. As indicated by the large standard errors, larger longitudinal studies are needed.Most genetic research has been consistent with this dramatic increase in heritability for intelligence in the early human life course. 55 GCTA analyses in the same study but using unrelated individuals yielded a highly similar genetic correlation of 0.73 (0.29) from age 7 to age 12. Most strikingly, a 60-year longitudinal study of intelligence, which was the first application of bivariate GCTA, yielded a genetic correlation of 0.62 (0.22) from age 11 to 69.46Why does the heritability of intelligence increase so dramatically from childhood to adulthood, as seen in twin studies? A clear yet apparently contradictory finding constrains possible answers to this question. Despite this great increase in heritability, the same genes affect intelligence from age to age. For example, a recent twin study reported a genetic correlation of 0.75 (standard error=0.08) from age 7 to age 12, despite increasing heritability from 0.36 (0.03) to 0.49 (0.04) and despite mean changes in brain structure and function from childhood to adolescence.genetic amplification.57 This has recently been supported in a meta-analysis of 11500 twin and sibling pairs with longitudinal data on intelligence that found that a genetic amplification model fit the data better than a model in which new genetic influences arise with time.58 Genotype-environment correlation seems the most likely explanation in which small genetic differences are magnified as children select, modify and create environments correlated with their genetic propensities. This active model of selected environments—in contrast to the traditional model of imposed environments—offers a general paradigm for thinking about how genotypes become phenotypes.59Thus, the question becomes, why does the heritability of intelligence increase during development despite strong genetic stability from age to age? That is, the same genes largely affect intelligence across the life course and yet genes account for more variance as time goes by. Increasing heritability despite genetic stability implies some contribution from what has been called 60 This is a surprising finding because very different neurocognitive processes appear to be involved in such cognitive abilities.25 Although these genetic correlations put intelligence at the pinnacle of the hierarchical model of cognitive abilities mentioned earlier, there is also genetic specificity that builds the genetic architecture for the rest of the hierarchical structure of group factors and specific tests.Another special genetic feature of intelligence is that its differences are caused by genes that affect cognitive abilities as diverse as, for example, spatial ability, vocabulary, processing speed, executive function and memory. Most of the genetic action lies with these general (highly pleiotropic) effects, captured by intelligence, rather than effects specific to each ability, leading to a Generalist Genes Hypothesis.18 Genetic correlations among cognitive tests are typically greater than 0.6, indicating that the same genes are responsible for the heritabilities of these tests.61 Genetic correlations estimate the extent to which genetic effects on one trait are correlated with genetic effects on another trait independently of the heritabilities of the two traits. They can be thought about roughly as the probability that genes associated with one trait are also associated with the other trait. Genetic correlations are derived from the genetic analysis of covariance between traits using the same quantitative genetic methods used to analyse variance.6In a meta-analysis of 322 studies, the average correlation among individual diverse cognitive tests is about 0.3.62 The genetic correlations  between intelligence and learning abilities are uniformly high: 0.88 (0.84–0.92) with reading, 0.86 (0.81–0.90) with mathematics and 0.91 with language (0.87–0.94). Weighting these genetic correlations by the heritabilities of the latent factors, it can be shown that about two-thirds of the phenotypic correlations between the factors can be explained genetically. One advantage of using such latent factors is that they exclude uncorrelated measurement error. As a result, these genetic correlations are higher than those found when uncorrected composite scores rather than latent factors are analysed: 0.66 (0.05 standard error) for reading, 0.73 (0.03) for mathematics and 0.80 (0.06) for language.63These general genetic effects permeate not only cognitive abilities such as spatial and vocabulary that are used as part of the assessment of intelligence but also extend to education-related learning abilities such as reading and arithmetic. 63 Within intelligence, the major group factors of verbal and nonverbal ability yielded a genetic correlation of 1.0 (0.32) in a bivariate GCTA in the same sample.64 The high GCTA genetic correlation between verbal and nonverbal based on unrelated individuals supported the twin study estimate of 0.60 (0.09) in the same study.The first attempts to use bivariate GCTA see  to verif63An important feature of bivariate GCTA is that it yields genetic correlations similar to genetic correlations estimated from the twin method, even though heritabilities are considerably lower for GCTA than for twin estimates. In the study just mentioned, GCTA heritabilities were consistently lower than twin heritabilities: 0.35 vs 0.47 for intelligence, 0.16 vs 0.59 for reading, 0.32 vs 0.48 for mathematics and 0.35 vs 0.41 for language. As noted in 66 Another reason might be that the evidence for this finding rested largely on the twin design, for which there have always been concerns about some of its assumptions;6 we judge that this will change now that GCTA is beginning to confirm the twin results.This finding of strong genome-wide pleiotropy across diverse cognitive and learning abilities, indexed by general intelligence, is a major finding about the origins of individual differences in intelligence. Nonetheless, this finding seems to have had little impact in related fields such as cognitive neuroscience or experimental cognitive psychology. We suggest that part of the reason for this neglect is that these fields generally ignore individual differences.67This finding of strong genome-wide pleiotropy across diverse cognitive and learning abilities is compatible with multiple neurocognitive models of causal pathways. The modularity model of cognitive neuroscience might suggest that genetic correlations among cognitive abilities are epiphenomenal in the sense that multiple genetically independent brain mechanisms could affect each ability, creating genetic correlations among abilities. However, the genetic principles of pleiotropy (each gene affects many traits) and polygenicity (many genes affect each trait) lead us to predict that generalist genes have their effects further upstream, creating genetic correlations among brain structures and functions, a prediction that supports a network view of brain structure and function.In summary, multivariate genetic research—both from twin studies and GCTA—suggests that most of the genetic action is general across diverse cognitive abilities rather than specific to each ability. Intelligence is a good target for gene-hunting because it indexes these generalist genes.68 and for weight,69 and about 0.10 for personality.70 For intelligence, assortative mating is about 0.40.71 Moreover, verbal intelligence shows greater assortative mating (~0.50) than nonverbal intelligence (~0.30), perhaps because it is easier to gauge someone's verbal ability such as vocabulary than their nonverbal intelligence such as spatial ability. Assortative mating for intelligence is caused by initial selection of a mate (assortment) rather than by couples becoming more similar to each other after living together (convergence).73 In part, spouses select each other for intelligence on the basis of education—spouses correlate about 0.60 for years of education19—which correlates about 0.45 with intelligence.50 Assortative mating may be greater than it is for intelligence for a few other traits such as social attitudes, smoking and drinking, although these traits might be affected by convergence. It should also be noted that not all of the genetic variance for intelligence is additive. For example, dominance, which involves interaction among alleles at a locus, is indicated by research showing inbreeding depression for intelligence.74 When assortative mating is taken into account in variance components analysis, some evidence for nonadditive genetic variance emerges.75Although the phenotypic correlation between spouses, assortative mating, might seem an esoteric topic, it has important implications for the genetic architecture of intelligence. Assortative mating is far greater for intelligence than for most other traits. For example, assortative mating is about 0.20 for heightThe significance of high assortative mating for intelligence is that assortative mating for polygenic traits increases additive genetic variance. Additive genetic variance refers to the independent effects of alleles or loci that ‘add up', in contrast to non-additive effects of dominance within a locus, and epistasis across loci in which the effects of alleles or loci interact. Assortative mating of parents increases additive genetic variance in their offspring because offspring receive a random sampling of half of each parent's genes and resemble their parents to the extent that each allele shared with their parents has an average additive effect. Because offspring inherit only one of each of the parents' pairs of alleles, offspring differ from their parents for non-additive interactions.76 equation 5, Table 10.6, p. 176.For example, if spouses mated randomly in relation to intelligence, highly intelligent women would be just as likely to mate with men of low as high intelligence. Offspring of the matings of women of high intelligence and men of low intelligence would generally be of average intelligence. However, because there is strong positive assortative mating, children with highly intelligent mothers are also likely to have highly intelligent fathers, and the offspring themselves are likely to be more intelligent than average. The same thing happens for less intelligent parents. In this way, assortative mating increases additive genetic variance in that the offspring differ more from the average than they would if mating were random. The increase in additive genetic variance can be substantial because its effects accumulate generation after generation until an equilibrium is reached. For example, if the heritability of intelligence with random mating were 0.40, the additive genetic variance of intelligence would increase by one-quarter at equilibrium given assortative mating of 0.40, Falconer and MacKay79 Moreover, GCTA heritability estimates are greater, although not significantly so, for verbal than non-verbal intelligence,80 which is consistent with the greater assortative mating for verbal than non-verbal intelligence. Third, because both GWA and GCTA are limited to detecting additive genetic variance, the GCTA estimate of substantial additive genetic influence on intelligence makes intelligence a good target for GWA studies.The extra additive genetic variance for intelligence induced by assortative mating is important for three genetic reasons. First, parents share only additive genetic variance with their offspring, so that genetic predictions from parent to offspring ought to be greater for intelligence when polygenic scores, composite scores based on associations of many loci with intelligence, are available. Second, because GCTA has so far been limited to detecting additive genetic variance, GCTA heritability should be greater for intelligence than for traits that show less assortative mating such as personality. Some evidence supports this prediction in that GCTA heritability estimates for personality appear to be much lower than for intelligence, even taking into account the lower twin-study heritability estimates for personality than for intelligence.81 This DNA estimate of genetic similarity between spouses is substantially less than assortative mating for education levels, suggesting that assortative mating may be driven by ‘social sorting processes in the marriage market'.81Two additional points about assortative mating for intelligence warrant mention. First, unlike inbreeding, which reduces heterozygosity across the genome, assortative mating is trait specific—it increases additive genetic variance  only for genes associated with the trait for which mates assort and its genetically correlated traits. Second, assortative mating induces a genetic correlation between mates for a particular trait to the extent that the trait is heritable, regardless of whether assortative mating is driven by genetic assortment or by environmental factors such as propinquity. A recent study using genome-wide genotypes showed that spouses are more genetically similar than two individuals chosen at random.82 Although many other traits, such as those related to athletic performance, are also normally distributed, the importance of high intelligence makes it especially interesting. Genetic exploration of the positive tail of normally distributed traits is important conceptually because it moves away from the notion that we are all the same genetically except for rogue mutations that cause disorders, diseases and disabilities.Unlike psychiatric and other disorders, intelligence is normally distributed with a positive end of high performance as well as a problematic end of intellectual disability. High intelligence is responsible for exceptional performance in many societally valued outcomes, as documented in long-term longitudinal studies.83 Most recently, in a study of 370 000 sibling pairs and 9000 twin pairs in Sweden from 3 million 18-year-old males whose intelligence was assessed as part of compulsory military service, not only was high intelligence (top 4%) just as familial and heritable as the rest of the distribution, a method called DF extremes analysis suggested that the same genetic factors are at work.84 DF extremes analysis focuses on the genetic causes of the average difference between an extreme group, however defined, and quantitative trait scores for the population, comparing the differential regression to the population mean for the co-twins of identical and fraternal twin probands.85 To the extent that genetics is found to account for this average difference , it implies that there is a high genetic correlation between the extreme group and the quantitative trait.60 In the Swedish study, DF extremes analysis showed that genetics explained about half of the mean difference between the high-intelligence group and the rest of the distribution, which was similar to the traditional heritability of individual differences and implies strong genetic links between high intelligence and normal variation in intelligence.Quantitative genetic research on intelligence indicates that the genetic causes of high intelligence are quantitatively, not qualitatively, different from the rest of the distribution. A recent study of 11000 twin pairs found that the top 15% of the intelligence distribution was just as heritable (0.50) as the rest of the distribution (0.55).86 The most persuasive argument for genetic discontinuity for extremely high intelligence was made by David Lykken who noted that a key problem of genius is ‘its mysterious irrepressibility and its ability to arise from the most unpromising of lineages and to flourish even in the meanest of circumstances' (Lykken87 p. 29). Lykken88 proposed that genius emerges from unique combinations of genes; he referred to these higher-order nonadditive (epistatic) interactions as emergenic. The emergenesis hypothesis does not necessarily predict that different genes affect high intelligence, but it does predict that genetic effects are non-additive for high intelligence. The hallmark of an epistatic trait is one for which identical twins are more than twice as similar as fraternal twins. However, in the two twin studies described above, high intelligence did not show this pattern of twin results and model-fitting analyses found that all genetic influence was additive for high intelligence as well as for the entire distribution of intelligence. Although these results do not support the Discontinuity Hypothesis, the studies were limited to the top 15% and top 4% of the intelligence distribution, which is far short of the extremes of genius, which Galton89 benchmarked as the top 0.1%.It is possible that scores more extreme than the top 4% of the intelligence distribution are aetiologically different from the normal distribution, which has been called the Genetic Discontinuity Hypothesis.90 However, extremely severe intellectual disability appears to be aetiologically distinct, as proposed by Lionel Penrose91 in 1938 and confirmed in the Swedish and Israeli studies. One critical piece of evidence is that siblings of persons with severe intellectual disability have an average intelligence quotient (IQ) near 100 whereas siblings of persons with mild intellectual disability have an average IQ of about 85, about one standard deviation below the population mean. The absence of genetic links between severe intellectual disability and normal variation in intelligence fits with current molecular genetic research that finds noninherited de novo mutations associated with severe intellectual disability.92The aetiology of high intelligence is also interesting in comparison to intellectual disability. Similar to high intelligence, most intellectual disability is the low end of the normal distribution of intelligence. This has been shown most recently in the Swedish conscript sample mentioned above, with results replicated in a similarly large conscript sample in Israel.de novo mutations as well as prenatal and postnatal trauma, but high intelligence requires that everything works right, including most of the positive alleles and few of the negative alleles associated with intelligence. This hypothesis is the rationale for a recent genome-wide case–control association study for cases with extremely high intelligence (IQ>150).84 However, one study93 has found no association between rare SNPs and intelligence in the normal range of intelligence. In addition, several studies have found no association between copy-number variants, which are typically rare variants, and intelligence in the normal range, although such studies may have been underpowered both in terms of sample and difficulties in assessing copy-number variants.94An hypothesis to integrate these genetic results for the low and high ends of intelligence is this: Normal development of intelligence can be disrupted by any of many mutations including non-inherited 95 It also raises the question of who these people are at the positive end of the polygenic distribution of ‘risk' for psychological and other traits. Are they merely individuals at low risk for problems or do they have special powers? Thinking positively begins by thinking quantitatively—about ‘dimensions' rather than ‘disorders' and about genetic ‘variability' rather than genetic ‘risk'.Although the normal phenotypic distribution of intelligence makes it an obvious target for investigating the high as well as low extremes, the larger significance of positive genetics for psychiatric genetics is that polygenic scores created from GWA studies of psychiatric disorders will be normally distributed, which means that there is a positive end with just as many people as the negative end. This implies that at the level of DNA variation there are no common disorders, only normally distributed quantitative traits.96 Education and social class are also well-established associates of health inequalities, including all-cause mortality.30 However, intelligence is a new player in health; its associations with many health and illness outcomes and all-cause and several specific causes of mortality have been discovered in the last decade or so.97It has long been known that intelligence, education and class are correlated. The causes of these associations and their relative contribution to social mobility is much disputed.99 Both, and the person's own adult social class, are associated with health, illness and mortality: less educated people and those in less professional jobs tend to die earlier.103 However, there is a third variable in social mobility research, and a third variable in health inequalities research: intelligence.104 Both education and social class are substantially correlated with intelligence.105We shall explain in this section that, akin to, but broader than cognitive and learning abilities, intelligence shares genetic causes with education and social class, which are touchstone ‘environmental' variables of diverse social scientists. Major human phenomena studied by these social scientists are social mobility and health inequalities, which are unarguably important. They are studied by sociologists, epidemiologists and economists. Finding out why some people more than others make positive progress in their social position through the life course, and why some people are more prone to illnesses and early death have drafted in the two favourite ‘environmental' social science variables of education and social class. Education and parental social class are predictors of people's social position in adulthood.106 but they are correlated with intelligence, which has a high heritability. Indeed, epidemiologists even use height—shorter stature is associated with earlier mortality—as an indicator of childhood social-environmental influences, though it has high heritability. For example, a recent social epidemiology article described height ‘as a marker of early life insults'.107 Here, we emphasise that it is an empirical question rather than something that can be assumed a priori as to whether the three key variables in social mobility and health inequalities research—education, social class and intelligence—correlate because of shared genetic and/or environmental causes.Education and social class  are often assumed to be indicators of a person's environmental influences,108 The genetic correlation was 0.65 (s.e.=0.02) between intelligence and education, 0.40 (0.02) between intelligence and deprivation and 0.48 (0.02) between education and deprivation. An earlier report on a smaller sample (N>6000) of the same study found genetic correlations between intelligence and being physically active outside work (0.25), fruit and vegetable intake (0.23), ever smoking (0.45), smoke exposure (0.53) and income (0.45), with high bivariate heritabilities for all of these.109 Another study identified over 2500 pairs of school-age twins from population samples totalling over 300 000 in England and the Netherlands and found moderate to large genetic correlations and bivariate heritability between intelligence and national examination results in language, mathematics and science.61 Analyses of older Danish twins found evidence for genetic correlation between cognitive ability and education and health.111Twin and family studies have shown that educational attainment and social class are somewhat heritable. For example, the pedigree-based estimates of heritability (here as percentages of phenotypic variance explained) in the Generation Scotland family-based study of over 20 000 people were 54% (s.e.=2%) for general intelligence, 41% (2%) for education and 71% (1%) for social deprivation using the Scottish Index of Multiple Deprivation.N~11 500) used GCTA to provide an estimate of 22% (s.e.=4%) for the heritability of years in education and 25% (8%) for attending college.16 In the Twins Early Development Study for 3000 unrelated children, GCTA-based estimates of heritability were 21% (12%) for parental social class and 28% (17%) for children's IQ at age 7 and 32% (14%) at age 12. The GCTA-estimated genetic correlation between parental social class and IQ was 1.00 (s.e.=0.47) at age 7 and 0.66 (0.31) at age 12.56 GCTA-based estimates of heritability on over 6500 unrelated people with genome-wide SNP data in the Generation Scotland study were 29% (5%) for general intelligence, 21% (5%) for education and 18% (5%) for social deprivation.112 The genetic correlations were 0.95 (0.13) for intelligence and education, 0.26 (0.16) for intelligence and deprivation, and 0.45 (0.18) for education and deprivation. Therefore, some of the variance in the social scientists' key environmental variables can be found in DNA variation, some of which is shared with the DNA variation that causes some of people's differences in intelligence. Another ‘environmental' social science variable, height, shows a similar set of findings in the Generation Scotland study sample.108 The GCTA-estimated heritability of height was 58% (5%), its phenotypic correlation with intelligence was 0.16, the GCTA-based genetic correlation was 0.28 (0.09), and the bivariate heritability was 71%. Bivariate GCTA-derived genetic correlations between intelligence and health variables will require large numbers which are rare, as yet. An analysis of data from the Swedish Twin Registry  found GCTA-derived genetic correlations of 0.13 (s.e.=0.23) and 0.33 (s.e.=0.33) between self-rated health and, respectively, years in education and attending college16).GCTA studies have recently explored the heritability and genetic correlations of intelligence, education and social class. A combined analysis of Swedish and Australian unrelated subjects 104 definition, that is, ‘the use of cognitive ability test scores as risk factors for human health and disease outcomes, including mortality'. Relevant to the genetic associations discussed in this section was Singh-Manoux's further discussion,106 this definition of cognitive epidemiology puts it squarely in the domain of social epidemiology, a discipline concerned with the social distribution of determinants of health. Location in this broader church, rather than the micro-discipline of cognitive epidemiology, will avoid a narrow focus on intelligence that ignores its associations with markers of social position such as education, income and occupation.'‘Given the association between intelligence and education, extensively discussed by Deary and Johnson,The genetics of intelligence has a special place, therefore, in the heretofore-named ‘social' epidemiology. Indeed, these new findings from twin/family-based and GCTA-based studies give a corrective to the suggestion that ‘cognitive epidemiology' be re-named ‘social epidemiology'. Singh-Manoux'svia genetic contributions to system integrity, allostatic load and the adoption of health-promoting/reducing behaviours.114One might say in reply that this conceptualisation ignores possible genetic contributions to social/cognitive epidemiology. To sum up: there are genetic causes of some of the educational and social class differences in the populations studied, and these overlap with the genetic causes of intelligence differences. Intelligence genetics is special here, because it offers the possibility of finding some of the connections between social and medical outcomes, perhaps These five special findings about the genetics of intelligence differences have emerged from traditional quantitative genetic research, primarily twin studies, and they are beginning to be replicated using GCTA. However, nothing would advance the field more than moving beyond GCTA to G, C, T, and A—that is, identifying specific DNA variants that contribute to the high heritability of intelligence. As is the case for all complex traits and common disorders in the life sciences, we now know that this will be a difficult task. As discussed earlier, GWA studies have shown that there are no large effect sizes in the population, which implies that the heritability of intelligence is caused by thousands of DNA variants, many of these effects are likely to be infinitesimal or even idiosyncratic. Nonetheless, GCTA has shown that additive effects of common SNPs can theoretically account for at least half of the heritability of intelligence, which means that a brute force approach using ever larger samples will identify some of these genes. In addition, whole-genome sequencing will identify DNA variants of any kind anywhere in the genome, not just common SNPs.genome-wide polygenic scores (GPS), as described in Associations of small effect size between DNA variants and intelligence can be summed across multiple loci to create a polygenic score, which is analogous to aggregating items to create a scale. Polygenic scores can aggregate a few candidate SNPs or thousands of SNPs across the genome, called Anticipating that GPS will be available for research on intelligence, we close by revisiting the five special findings about genetics and intelligence, drawing hypotheses that can tested using a GPS for intelligence, an exercise that we hope will help to make the five special findings more concrete.GPS hypotheses follow directly from the finding that the heritability of intelligence increases throughout the life course despite strong genetic stability from age to age: Variance explained by a GPS should increase with age, and a GPS discovered at one age, adulthood for example, is expected to predict intelligence at other ages such as childhood.115A GPS hypothesis follows directly from finding strong genome-wide pleiotropy across diverse cognitive abilities: A GPS that is discovered for any cognitive or learning ability should also predict any other ability. Also, a GPS for intelligence should predict better than a GPS for any other trait. It has been suggested that a pleiotropic GPS that explictly targets the substantial covariance among diverse cognitive and learning abilities will be even better than a GPS based on a single composite measure of intelligence.GPS support for the previous two hypotheses seems likely because preliminary GCTA results discussed above already provide some support for these hypotheses. In the case of assortative mating, GPS could provide a novel test of the extent to which assortative mating for intelligence is mediated genetically by correlating GPS between spouses. Another question that emerges from previous genetic research is whether GPS assortative mating is greater for verbal than for nonverbal ability.Finding that the same genes affect high intelligence to the same extent as the rest of the normal distribution leads to the hypothesis that a GPS for intelligence from unselected samples can also be used to predict high intelligence.Finding that, in twin and GCTA studies, the same genes influence intelligence and social epidemiologists' ‘environmental' variables of education, social class, and height can enlighten research in health and social inequalities. It leads to the hypothesis that GPS scores for intelligence might contribute to health outcomes and mortality, and that these might account for some of the associations between education and class and mortality.


LIB) approach. However, in some cases recommendations to refrain from this approach have been made. Here we test if a common widespread species with no obvious signs of local adaptation may be a candidate species for abandoning LIB during restoration. Using 10 microsatellite markers we compared population genetic patterns of the generalist species Daucus carota in indigenous and formerly restored sites . Gene diversity overall ranged between He = 0.67 and 0.86 and showed no significant differences between the two groups. Hierarchical AMOVA and principal component analysis revealed very high genetic population admixture and negligible differentiation between indigenous and restored sites (FCT = 0.002). Moreover, differentiation between groups was caused by only one outlier population, where inbreeding effects are presumed. We therefore conclude that the introduction of nonlocal seed provenances in the course of landscape restoration did not jeopardize regional species persistence by contributing to inbreeding or outbreeding depressions, or any measurable adverse population genetic effect. On the basis of these results, we see no obvious objections to the current practice to use the 10‐fold cheaper, nonlocal seed material of D. carota for restoration projects.For restoration purposes, nature conservation generally enforces the use of local seed material based on the “local‐is‐best” ( In landscape and roadside verge restoration projects the use of nonlocal seeds has been – and often still is – common practice, as prices for nonlocal seed mixtures can be up to 10‐fold lower than for local provenances, and often large quantities of indigenous genotypes are unavailable  was chosen for this study due to (1) its wide use in seed mixtures for herbal reintroductions, (2) its native abundance in a broad range of habitats, and (3) its common presence in the investigation area. Typical habitats of D. carota are meadows, thickets, and areas along railroads and roadsides with some kind of disturbance, while the species is also common in extensively managed grasslands. The species' native distribution covers large parts of Europe, Eastern and Central Asia, and the Mediterranean region with up to 10 poorly defined subspecies , microsatellite markers, and amplified fragment length polymorphisms (AFLP) – mainly focusing on cultivars or germplasm variability  situated in Central Germany  within an investigation area of approximately 200 × 200 km2 in a comparatively sparsely populated hilly region. R‐sites cover an area between 0.5 and 2 ha and were restored between 1996 and 2004 .As the main motivation for site selection was good documentation of site history, populations are not regularly spaced throughout the investigation area. For each site, information about the year of restoration as well as the presence and percentage of R‐populations excluding the outlier R04.During data analysis the restored site R04 turned out to markedly differ from all others site. Hence, some calculations were additionally executed for a subset of I), as representatives of the local genotypic diversity: four meadows which are mostly maintained under the Habitats Directive of Natura 2000, and five protected nature reserve areas , 1 μL reverse primer (5 pmol/μL), 0.4 μL BSA (10 ng/μL), 4μl Betain Monohydrat (5 mol/L), 2.4 μL dNTPs (2 mmol/L), 0.5 μL (5 U/μL) DreamTaq polymerase , 2 μL 10 × DreamTaq PCR buffer (Fermentas), and 1 μL of the diluted genomic DNA. PCR was conducted with an Eppendorf‐Gradient‐Mastercycler. The PCR program was 2 min at 95°C for initial denaturation, followed by 35 cycles of 30 sec at 95°C, 30 sec at the annealing temperature of each primer pair  was applied according to the manufacturer's instructions. DNA was diluted to 3–10 ng/o et al.  for its on Table . The PCR® V1.90 . The lengths of the DNA fragments were standardized using ROX 500. For evaluation, fragments were recorded in a codominant data matrix. Genetic diversity within populations was estimated as number of different alleles (Na), number of effective alleles (Ne), Shannon's information index (H′), and observed (Ho) and unbiased expected heterozygosity (uHe) using GenAlEx 6.5 . Genetic variation among groups of indigenous and restored populations (FCT), among populations within groups (FSC) and within populations (FST) was partitioned with hierarchical analysis of molecular variance (AMOVA) using ARLEQUIN 3.5.1.2 . Highest number of effective alleles (Ne) and highest He values were found in an indigenous population . In contrast, highest number of different alleles (Na) was found in a restored population . Lowest Ne, I, Ho, and He were found in population R04. Single sample t‐tests revealed R04 to diverge significantly from all other populations . However, the equality of variances between all indigenous and restored populations with or without R04 was not affected (P < 0.05).Overall, 86 Table  with an FST = 0.030, P < 0.01) was lower than among restored populations . However, again excluding R04 from the dataset led to comparable values for restored sites , substantiating the different population genetic pattern of R04 , whereas only 4.1% explained differences among populations within groups and only 0.2% among indigenous and restored populations  and in one restored site (R05), which was established in 1998. As no information about the initial genotypic diversities of the nonlocal seed mixtures at the restored sites are available, it remains rather speculative if the current findings are the results of slightly lower initial genotypic diversities in the seed mixtures or are due to selection processes in the new habitats.D. carota only remained as a remnant within grassland on the margins of the site, where other dicots are scarce, too. Due to intensively used agricultural fields in close vicinity, there are no other potential habitats for D. carota within a radius of 1 km. Even if we consider that pollinators do have longer flight ranges, site visitation for pollination might be comparatively rare.The lowest allelic diversities were found in one restored population R04, which diverged substantially in its population genetic pattern from all other investigated sites. Restoration of R04 took place in 1996 together with population R03, which is in close vicinity. The executing authority was in both cases the same. Thus, the detected difference in population genetic diversity is rather unlikely to originate from differences in the initial seed mixtures. The comparatively low values of within‐population diversity with the extremely low values of different alleles and effective alleles in R04 could be indicative for high inbreeding. R04, with approximately 1 ha, is nowadays predominantly covered in scrub vegetation (approximately 80%) and Cichorium intybus L., and discovered high genetic similarity in populations from Germany, Italy, Croatia, and Uzbekistan, even with increasing geographic distances. Thus, as population genetic diversity is the result of the accumulations of neutral substitutions or diversifying or frequency‐dependent selection, one might have to refer to “nonlocal” as a sweeping term, dependent on the degree of adaptation and selection in the respective target species, without narrowing it down to geographic vicinity, which currently is the common approach in many nature conservation strategies.We found no obvious signs that the introduction of nonlocal seed material in the course of restoration purposes contributed to the regional overall genetic diversity of the species. This finding is in contrast to current assumptions that “the diversity of the original source population is a critical consideration for restoration purposes, and that the starting pool of genetic diversity governs the performance of a reintroduced population for a long time” (Falk et al. For restoration practitioners the use of local seeds has become a common objective (e.g., Broadhurst et al. D. carota. In the obligate outcrossing plant species we could detect negligible population differentiation between indigenous populations and populations restored with nonlocal seed material. No negative effects on allelic richness, selective sweeps, or reduced population genetic diversity could be observed, with one exception, where inbreeding effects are presumed. Even though no information about the geographic origin of the “nonlocal” seed material is available, we assume that for the common, outcrossing and generalist species the term “nonlocal” is a sweeping term which should not be narrowed down to geographic vicinity, as presently common in biodiversity conservation.By using molecular tools to evaluate landscape restoration projects on compensatory sites several years after establishment we could demonstrate that the use of nonlocal seed provenances did not result in adverse population genetic effects on indigenous populations of D. carota. Moreover, this might also be the case for other common, generalist and outcrossing plant species.Decisive criteria for restoration projects are restoration objectives and goals, as well as the efficient use of resources considering costs and seed availability (Ehrenfeld Data for this study are available at: to be completed after manuscript is accepted for publication.None declared.


Genetic counselling is “a process of communication that deals with the occurrence, or risk of occurrence, of a (possibly) genetic disorder in the family” . It involves an attempt, by appropriately trained persons, to help patients and their families to (1) understand the medical facts of the disease; (2) appreciate the contribution of heredity and risks of recurrence in relatives; (3) understand the consultands’ options to deal with those risks, including all their reproductive options; (4) use this genetic information in a personally meaningful way that promotes health, minimizes psychological distress and increases personal control; (5) choose the course of action that seems appropriate to them and act in accordance with that decision; and (6) make the best possible adjustment to the disease or the genetic risks .Genetic counselling must always begin with the establishment or documentation of a clinical and genetic diagnosis in a proband, followed by counselling of relatives at risk. In the context of presymptomatic testing (PST), i.e., in healthy relatives at high-risk for a late-onset monogenic disease with high penetrance, as ATTR amyloidosis, a protocol of pre- and post-test genetic counselling needs to be offered; and be accompanied by psychosocial evaluation and support, their purpose being to assess motivations for testing, explore decision-making processes, test coping mechanisms, predict risk of adverse emotional reactions, prepare psychosocial support, identify values and family dynamics and reinforce social support networks. Family’s experience (late vs. early-onset) is critical. PST should begin with relatives at higher risk (cascade testing). Minors should not be tested, as they might lose their autonomy and suffer discrimination. In the context of diagnostic testing, neurological symptoms must be evident, so that the genetic laboratory does not perform an inadvertent PST. In the context of prenatal diagnosis (PND) or of preimplantation genetic diagnosis (PGD), both parents must be involved in the counselling protocol, one of them must be affected or a presymptomatic carrier, with a TTR mutation previously identified in the family; in addition, for PND, there must be a clear motivation for termination of pregnancy if the foetus is a mutation carrier.Availability of therapies and ongoing clinical trials may be a  motivation for increased adherence to PST; however, this is not relevant for treatment (will change when preventive measures or presymptomatic treatment become possible). ATTR amyloidosis, though potentially treatable, is still currently incurable . Genetic counselling is always mandatory.


Using data from focus groups conducted in Colombia, we explore how educated lay audiences faced with scenarios about ancestry and genetics draw on widespread and dominant notions of nation, race and belonging in Colombia to ascribe ancestry to collectivities and to themselves as individuals. People from a life sciences background tend to deploy idioms of race and genetics more readily than people from a humanities and race-critical background. When they considered individuals, people tempered or domesticated the more mechanistic explanations about racialized physical appearance, ancestry and genetics that were apparent at the collective level. Ideas of the latency and manifestation of invisible traits were an aspect of this domestication. People ceded ultimate authority to genetic science, but deployed it to work alongside what they already knew. Notions of genetic essentialism co-exist with the strategic use of genetic ancestry in ways that both fix and unfix race. Our data indicate the importance of attending to the different epistemological stances through which people define authoritative knowledge and to the importance of distinguishing the scale of resolution at which the question of diversity is being posed. These people were located at diverse distances from the specialist field of population genetics – they included humanities students, Afro-Colombian activists, life sciences (LS) students, forensic technicians and criminal investigators.Our article makes two central arguments, both of which highlight how publics engage with genetic knowledge about human diversity in very uneven ways. First, in terms of the weight attributed to genetics in shaping individual and collective identities and behaviour, and especially in terms of the status accorded the concept of race, there was a marked divergence between those who came from a humanities background or were race-critical Afro-Colombian activists and all the others in the FGs, who were varied but generally had LS training or were involved with genetics in their work. Even though both sets of people agreed on some fundamental ideas about the Colombian nation and its diversity, they used genetic and racial idioms to markedly different degrees. This may seem predictable, but the current literature does not generally highlight the need to nuance ideas about how genetics is or is not shaping ‘public’ perceptions, according to the epistemic viewpoints of different segments of the public but see .Second, among those more disposed to accord genetics a high degree of authority and weight – who are the main focus of this article – there was a significant difference depending on whether they were thinking on a collective level, about Colombia as a nation seen in terms of a racialized regional diversity, or on an individual level, in terms of personal identities and constitutions. At the individual scale of resolution, there was a good deal of flexibility: many other factors shaped the person, and genes might be expressed or remain latent. This suggests that, in assessing patterns of ‘geneticization’ in society, we need to be attentive to the specific domains in which people are imagining and plotting relations of being and belonging.The literature on the relations between genetic ancestry data and social identities has often been concerned with whether recent genomic science fosters the genetic reification of belonging and identities of ethnicity, race and nation . An initIn addition, social categories of race, ethnicity and nation have long circulated among different specialist scientific fields – population genetics, forensics, medicine and so on – and between specialist scientific and non-scientific domains – government, media, popular culture and so on. In the process, race both acquires and sheds genetic and other biological meanings. The specialist scientific sphere is not divorced from other less specialist domains, because: genetic information circulates into those domains, via a self-consciously public science; social categories are used to organize sampling and data; and geneticists and other people are interested in explaining the same kinds of problems – albeit in different ways – about health, belonging, history, roots, appearance, heredity and diversity . Thus, aAs a result, the relation between genetic ancestry data and social identities is an ambivalent, ambiguous and multivalent matter . GeneticOur research builds on these studies, but pays special attention to how engagement with genomic data varies according to people’s epistemic positioning on the spectrum of knowledge production, and also according to the scale of the problem of diversity they are pondering. We explore audiences that, while many had some knowledge of genetics in general, did not generally have a previous interest in genetic ancestry and were not members of associations for patients with genetic disorders or of ethnic groups with a stake in tracing ancestry . While sWe present data from a variety of FG participants – mostly students and thus well-educated and relatively young – and indicate the divergence between humanities students and Afro-Colombian activists, on the one hand, and people with an LS training, on the other. But we have chosen in this article to focus in particular on the latter category, which includes university students of the natural sciences and medicine in Colombia and some forensic technicians and criminal investigators, who had more direct experience with genetics – although not usually with genetic ancestry testing. Our interest in this group of people derives from their location in the ‘certainty trough’ , in whic2 All of the participants have been anonymized. The FGs drew participants from four constituencies: university students, forensic technicians, volunteers in a genomics research project and Afro-Colombian activists (themselves university students). As noted above, we draw a broad contrast between ‘life sciences’ people and the ‘humanities and social sciences’ people. We label these broad groups ‘LS people’ and ‘HS people’, respectively. It may be objected that the composition of the FGs pre-determined to some degree this interpretive contrast, as dynamics within FGs can lead people who share some attitudes to emphasize consensus. Against this, we note that (a) the LS and HS sets were heterogeneous. Each set comprised two or three sub-categories of people; and (b) these two sets concurred on some things and differed on others: there was not a binary contrast on all issues.The ideas presented here are the product of 45 FGs or group interviews done in the cities of Medellín and Bogotá in 2011–2012.The LS people comprised the following sub-sets:University students of medicine and biological sciences, selected from five universities in Bogotá.Forensics. These participants included users and producers of forensic genetics at the Instituto Nacional de Medicina Legal y Ciencias Forenses , the Fiscalía Nacional (Public Prosecutor’s Office) – laboratory technicians and attorneys – and members of the national police force’s School of Criminal Investigation.LATINA. The respondents in this group were participants in an international project that was collecting anthropometric measurements and genetic ancestry data on samples of Latin Americans and complementing these data with participants’ self-perceptions of ancestry. In Colombia, this project was being carried out at a public university in Medellín. Most of these participants were university students, and most of them in the LS, but this group was more diverse, including some with no specialized LS background, for example high-school students, an amateur genealogist and even a self-declared White supremacist. Most participants had attended an introductory LATINA lecture on population genetics.The HS people comprised these sub-sets:University students in anthropology, literature, history and pedagogy from one university in Bogotá.Afro-Colombian activists. Members of Afro-Colombian social movements, based in Bogotá, with a diverse range of political interests and agendas linked to the better recognition and socio-political inclusion of Afro-descendants in Colombian society.A few of the LATINA participants, as noted above.Participants whom we cite are identified by their FG, using the letters ‘FG’, followed by the word Forensics, LATINA, Afro-Colombian, or University. The University category is divided into LS groups (lettered A to E) and the humanities groups (lettered H-1 and H-2). The individual groups are presented in a list at the end of the article.mestizaje , nation, genetics and Colombia. We usually started with mestizaje, as this is a foundational concept for many Latin American ideas of nationhood, evoking the narrative that the nation was based on the biological and cultural mixing of European colonizers, indigenous Americans and African slaves; other notions then followed spontaneously. The second segment elicited participants’ ideas regarding genetic, racial and national difference through images that had been selected from accessible arenas of mainstream Colombian society, such as TV publicity about the national census (which in 2005 included a question designed to identify Afro-Colombians and indigenous peoples), and antiracist and human rights campaigns available on the Internet and on many billboards around Bogotá and Medellín. Finally, the activity ended with a mock genetic ancestry questionnaire (Our FG sessions were divided into three segments. The first section used words and spontaneous associations to ascertain how people conceived of key notions such as ionnaire . In thisindígena), Black (negro) and European (europeo). This was mainly because LATINA researchers believed that people would tend to avoid identifying ‘African’ ancestors, resulting in an underestimation of people’s perceptions of their Black African ancestry. The Spanish neologism ancestría (ancestry) was used in the table, a word which was unknown for most respondents, hence the explanation given in the table in terms of ‘your ancestors’. However, participants generally inserted the concept into their vocabulary, readily linking it with the more common concept of ascendencia .It is notable that the table used disparate categories: indigenous (negro), while major areas of the Andean highlands are seen as predominantly mestizo and White (blanco). Ideas about racialized appearance and ancestry are often articulated in the idiom of regional difference. However, the word and concept of ‘race’ are not straightforward. Generally, we found that, when asked directly about race, participants in all the FGs spontaneously linked the term race to notions of purity and thought that in this sense, ‘race’ deserved to be treated with care in a country in which no one could be considered pure: ‘todos estamos mezclados con todos’ . Many participants decided that since admixture was so generalized, races, in the sense of pure types, did not exist anymore. Others, including a few LS students, more radically defended the idea that races had never existed, citing the Human Genome Project’s finding that all humans are genetically very similar. Race was also debunked when humans were compared to other animal species: ‘very visible physical differences make it possible to talk about different races of dogs, but not persons’ (FG-University D).In Colombia, race and region are closely linked, so that specific regions have powerful racial connotations . For exaracism was wrong.HS people strongly resisted using the word ‘race’ and had real difficulties talking about the biological dimensions of heredity in the context of race and/or genetics. These participants commonly depicted race as ‘a social construction’, which sorted phenotypic diversity into arbitrary categories, used since colonial times to divide and oppress indigenous and Black people in Colombia. Their background in the humanities made linking race to genetics appear to them a politically retrograde and suspect move. As one humanities student said: ‘when genetics participates in the making of racial categories, it is participating in a discourse that is not naïve at all’ (FG-University H-1). Above all, all FG participants – except the White supremacist – were united in the view that Yet many FG participants across the board used racial descriptors  when talking about the diversity of Colombians and linking diversity to regional variation; some also used the term ‘race’ itself. As we show in the next section, a clear contrast emerged here between LS people and HS people.When it came to the relation between ancestry, genetics and race, the LS people tended explicitly to see race as related directly to genetic ancestry or genetics more broadly:ESM:So would you say that genetic ancestry is the same as race?Student 1:I would say so, yes.Student 2:It all depends on the definition of race you have, but I would definitely say that genetics [i.e. a genome] is the mixture of many races [i.e. ancestries]. (FG-University C)Yet most LS people also commonly elaborated on how regions configured people’s biology, culture and inclinations. Regional notions of difference organized the way bodily features, temperaments, dispositions and lineages were seen as linked to specific places inside the Colombian nation. In most cases, too, global geography implied race, and continents or regions of the world were immediately associated with a racial or colour group. Region was often linked to a specific genetic collective mark, as the following excerpt illustrates:Student 1:Of course race and region coincide, because regions are different, if one region is hotter, then this will come out in the genes, genes will be of different colour …Student 2:When you say black, Africa comes to my mind …Student 3:Or when you say indigenous, Mexico, Bolivia or Peru come to my mind …Student 1:I relate the white race with cold geographies, you know in the north and all those places …ESM:So you think there is a relation between geography, race and genetics, right?Student 4:Clearly there is a relation, if it was not the case there would be no heredity. Black parents could have a son with the phenotypical characteristics of a Chinese person. For me there is a clear relation, which is highly influenced by environmental and geographic factors that influence the appearance of a certain phenotype. (FG-University B)paisas3 from Medellín, Antioquia (in the north-west of the country), were seen as a good example of whiteness, while people from the Chocó province of the Pacific coastal region were commonly depicted as belonging to a Black lineage or population that might even be seen as relatively ‘pure’, despite the explicit disavowal of pure races. Indigeneity was located in the southern and Amazonian provinces of Colombia. Paisas and Chocoanos were seen as opposing poles in the national imaginary .Whiteness, blackness, indigeneity and admixture all have their corresponding original places inside Colombia, according to these informants. Typically the If we talk about biology, we can only define the human race, the others are socially constructed to differentiate according to phenotype, and give more cultural attributes to some people, and generate inequality, assuming that the white race is superior and from there … the others are below, like in a pyramid. (FG-Afro-Colombian)HS people also recognized the regional diversity of the country and the links between, say, blackness and the Pacific coastal region, but they tended to resist talking about this diversity explicitly in terms of race and, more so, genetics; instead, diversity was expressed in an idiom of culture. In addition, they tended to see regional distinctions as stereotypes that categorized phenotypic diversity in ways linked to power and cultural hierarchies. For example,Still, even among the HS people, the common-sense links between regions and cultures were implicitly racialized, as – like most Colombians – they linked blackness, indigeneity and whiteness to specific certain regions of the country, even as they generally avoided the language of race and, especially, genetics. For both HS and LS people, race as purity was disavowed, but re-emerged via a link with regional difference in the nation. The difference was that the LS people made direct links between diversity, racialized genetics and region; the HS people linked diversity and region together, leaving the element of racialized genetics submerged.Races on the Colombian coasts tend to be different from the people and races from the interior, we tend to see black races on the coast, and in the interior we are more pink- and white-looking and when you move to the south more types of indigenous races become apparent … within regions, people share a common background, heritage, customs and genetics, and I think that when it comes to Colombia, it is more a territorial, political division than anything else … a history in common, and some ideas of course, but that is all. (FG-University B)I think Colombia does not have a particular genetic structure, I would say we share some customs and another few things but that is all … and maybe some cultural traits, but something like a characteristic Colombian genetics? No! (FG-University C)The symbolic power of region was highlighted by the relative emptiness of the nation, seen as lacking unifying traits of Colombianness, which emerged from all our FGs. For the LS people, this was reflected in genetic as well as cultural terms: it was deemed possible to talk about the genetic composition of regional groups such as the Paisas, but it was nearly impossible to talk about the genetic composition of the average Colombian person:For the LS people, even the possibility of purity itself re-emerged when we asked participants how they imagined genetic ancestry test results were produced by geneticists. These participants consistently answered that a ‘real’ or ‘pure’ African, European or Amerindian referent was used to define how much of each ancestry each individual had. These genetic referents were usually thought to be living in faraway places like Norway or sub-Saharan Africa, but many times relatively ‘pure races’ were thought to exist in indigenous, White or Black communities inside Colombia, said to be fundamentally a nation of mestizos. The Pacific coastal region, indigenous reservations and highland Antioquia were consistently seen in the LS FGs as places in which regionalism and a strong sense of belonging had kept genetic lineages relatively pure. Depicted as endogamous and closed off, these communities were seen as pure in comparison to ‘hot spots’ of recombination (mostly big cities). Bogotá was seen as having lost its sense of community and any endogamous mating practices (and thus a distinctive genetic profile). Many participants stated that ‘the most difficult thing to find in Bogotá are people who are originally from Bogotá’ (FG-University A).moros  lived for a thousand years in Europe. (FG-Afro-Colombian)We think that when we talk of Africa, we talk of black people only, and that in Europe they are all white. But that is not the case: migrations and mixture have occurred there too. As it happens, in history those mixtures are erased; we should not forget that the In contrast, HS people challenged more systematically the idea of purity:mestizaje had undermined purity, and, as a consequence, race itself, was tempered by the continuous invocation of strong associations made between region and race. These links were made implicitly by the HS people and more explicitly by the LS people, who tended to invoke a genetic idiom as well.Nevertheless, in all our FGs, the idea that extensive Once I read at school that if the fourth generation of a person lives in a totally different environment from his ancestors, then that person would acquire some physical characteristics of the persons surrounding him. That is why we see that many black people who live in the United Kingdom are different from those living in Africa: for example their skin changes, they are not as black, not what you’d call really, really black anymore. Despite the strong stereotypes that configure the Colombian nation(s) and the racialized populations inhabiting their so-called natural regions, when it came to the configuration of the individual the role of race and genetics was not fixed in a pre-determined way. In this section, we focus on the LS people and how they describe individuals as the product of fluid interactions between the environment and their genetic or ancestral baggage. For example, one of our participants stated,mestizaje in Colombia had been so thorough that almost any individual you picked would have a variety of Black, indigenous and White ancestors, a combination that introduced unpredictability.She timidly added: ‘You might think I am crazy, but it seems to me that dark people become whiter as they become wealthier. … I can’t really explain how this happens but it kind of does’. For many LS participants, the individual could be understood at one level in terms of inter-connected aspects of race, genetics and appearance, but his/her individuality was constituted by multiple genetic, environmental, spiritual and socio-economic influences. Race was just one of many factors and, while at the regional level certain regular patterns were perceived to prevail, at an individual level things were much less predictable. It was believed that I think that likes and cultural traits are also hereditary, and I guess you could say genetic as well. … It has happened to me that you like something, and you don’t know why, and then you look and you find that someone else in the family liked that. (FG-University E)Genetics and heredity were still deployed to explain particular experiences. A lot of participants talked about their spiritual and cultural affinities, and how they were rooted in a genetic background:Such ideas could also be powerfully racialized at an individual level. Blackness was believed to be a lot more persistent than whiteness or indigeneity, in terms of heredity, and if it was thought to exceed 5 percent or 10 percent of genetic ancestry it was deemed to be very visible in the features of the individual. On the contrary, indigeneity and whiteness were easily diluted, even if both were seen as more common among Colombians than Black or African ancestry. Latent traits, in the specific case of blackness, emerged, according to many of our informants, when they were exposed to what they considered to be iconic Black cultural products and practices: ‘When I hear the drums I feel like I am from over there: I guess that I have something black inside me’ (paraphrased from FG-University C and FG-Forensics A).mestizaje, participants in our research resorted to three interpretative frameworks to define ancestry: somatic features, region and surname. The first and most common framework was a somatic reading of themselves and their families, which assigned certain parts of the body and face to racial groups. For example prominent bone cheeks were almost always related to having the look of an ‘indiecito’ (‘little Indian’); dark skin, a broad nose and a big or prominent behind (in both men and women) was almost always associated with being ‘Afro’ or ‘black’; and being ‘mono’ (fair-skinned) and ‘ojiclaro’ (green- or blue-eyed) was, not surprisingly, linked to being White or European. However, some somatic features, such as dark skin, occupied a more ambiguous space between ‘indigenous’ and the ‘black’ on the racial spectrum. Thus, there was plenty of room for debates about and interpretations of ancestral-somatic markers.In order to organize the many possibilities opened by the all-encompassing idea of Most commonly, such ambiguities could be resolved by adding the two other interpretative frameworks – region and parentage/surname – to the equation (FG-University D):Student A:I did it based on my last names, because I know the origin of my last names, therefore I gave myself 65% European ancestry, no indigenous ancestry, and 35% black ancestry.Student B:Well, I consider myself to be 40% indigenous, 40% European and 20% black. I know that I don’t look black, but where I come from 60% of the population is black, and in my family my grandmother is not white. I don’t even know why I was born so white.Student C:4I can’t decide yet. I would be 75 indigenous, 25 European, because my dad is from Tolima, and that is a region with a lot of indigenous communities, but as it happens he has green eyes, and I met my grandmother from my dad’s side and she had lots of indigenous features. On my mother’s side my grandparents are white; white and blue-eyed. The story I have heard is that they came from Santander.el paisita (the little Paisa): the claiming of indigenous ancestry sent a clear message to his peers that he was not the ‘racist Paisa’ of Colombian regional stereotypes.Some informants counter-balanced what others might, by looking at them, deem to be their ancestral baggage by making reference to the physical characteristics of immediate ancestors. For example Student C used the bodily features of parents and grandparents to justify his ancestry, instead of reading it directly from his body. Some of those with medical and biological training used medical terms to justify ideas about their ancestry that seemed intuitively to contradict their somatic appearance. For example a medic told us: ‘Of course I have indigenous heritage, I have black eyes and my blood is type O+, something that is quite typical of indigenous people’ (FG-University A). This student’s accent and appearance led his Bogotá peers to nickname him I gave myself indigenous ancestry, because indigenous people are our common lineage, I identify with them, that is what is characteristic about Colombia, they are our roots, it’s a personal taste. I decided in part by affinities with some things. … The 20% of black I gave to myself, I did based on the time I spent living in the Caribbean coast, and I was much more sympathetic than what I initially thought to their food, their housing, the sea. So I said: this must be because of a black ancestor. Somatic visible differences revealed the invisible (underlying) genetic reality of racial mixture, but not all genetic realities were expressed in the body. For example, someone who identified himself/herself with a certain region, family name and physiognomy as belonging to the category of ‘white-European’ would balance – or domesticate – this somatic reading with his/her own predilections for African rhythms or ideas about indigenous groups as the original people of Colombia:These predilections and affinities revealed origins in a different non-somatic way, tied to personal experiences. However, some of our informants thought that genetics could finally prove or disprove these origins and believed that these inclinations were rooted in a genetic heritage. In the same sense, ascribing personal likes to genetic heritage was acceptable, or at least was not contested by other peers in the FGs.Yes, because it has been seen that there are genes that modify the behaviour of a person, it has been seen that certain genes will give you your physical characteristics or [there are] genes involved in culture. (FG-University E)It is just that DNA is everything. In sum, then, LS respondents, who easily linked race, place and genetics in quite mechanical ways when talking at a regional scale, deployed much more varied and flexible ideas about heredity when it came to explaining individual constitutions and identities, which brought them much closer to HS people. People brought different objects and elements of meaning – race, genetics, experience, place, predilection, parentage – into and out of proximity with each other, in flexible ways that submerged some elements, perhaps temporarily, while leaving a trace of their presence and the possibility of their reappearance.This flexibility at the individual scale of resolution could co-exist with a strong belief in the reliability of genetic knowledge, which was especially evident among the LS people, but was also present among others too, in terms of believing in the power of genetics to reveal hidden ancestry in the individual.  People with LS backgrounds were especially confident about the reliability of DNA:RC (associate researcher):So what would make this blood sample different from other types of data about your origins or genealogy?Participant:a simple vista (just by looking). (FG-LATINA B)Because this is like a finger print, which is not going to be the same information that a person can give to you. It characterizes you in a special way. It gives you a register of what you really are! That means it is more definitive. I, as a biological engineer, know that there are genetic sequences that determine me, genetic markers that are used to do this type of research. It allows you to know characteristics that you cannot perceive The genetic tests carried out by the LATINA project scientists brought to the politics of belonging and identity calculable proportions of DNA, which could be seen as revealing a different and more ‘objective’ type of connection between history and a sense of communal and personal identity. This was illustrated during FGs when we asked about the differences between genetic science and other types of genealogical knowledge:RC:So what makes the difference between genetics and, say, a genealogy?Participant 1:It is the difference between the objective and the subjective. History alone can just explain to a certain level, there will always be limits. It [history] will never tell me, for example, you are from Achilles’ lineage. And genetics can. It provides much clearer percentages.Participant 2:The historian is subjective, many persons can think many things, and everyone has their truth, and defends it, but the sample says ‘this is that, and behaves that way’; it is a tangible and logical manner to show what you really are. Although both can be complementary. (FG-LATINA A)mestizaje opens up an unpredictable range of genealogical possibilities, added to the indeterminacy around DNA at the individual scale of resolution.This faith in the reliability of genetic science was, however, tempered by concepts of latency and manifestation, according to which genes might express themselves or lie dormant. These ideas appealed to people with LS training, who could talk in terms of recessive and dominant alleles; but they also made sense to those from other backgrounds, who thought inherited traits could express themselves, perhaps unexpectedly, or remain latent – ‘I heard it is common for phenotypic traits to remain dormant, and then appear again in the third generation’ (FG-University H-2) cf. . These cI would think that maybe the little proportion that I have of European ancestry is determining my physical features, and the rest of my ancestry is determining genes that are not expressed phenotypically, that are not expressed in the colour of hair or in the colour of my eyes. I am going to go to the scientific field: practically about 90% of the genome is not expressed; the other 10% is functional. As I understand it, to determine ancestries you use SNPs [single nucleotide polymorphisms] that are part of non-codifying sequences of the genome, that is information that is going to be stored [in the body], and that you think will never become manifest, but equally it is going to mark your heredity, so these are genes that you have stored there, forgotten, but there. (FG-University C)It is just that skin colour is affected by many factors: what I see is only a small reflection of what I have inside. In a way it is cultural, the black skin colour and broad nose are very suggestive of someone having black ancestry. But it is just that, suggestive: it does not mean that his/her genetic composition is always that. For example I have a brother with a very different skin colour, but I would not say we come from different places. Instead, I have to differentiate that one thing is what I am phenotypically, and another thing is what I am in my ancestry, where I come from. (FG-University B)Latency was used to explain counter-intuitive results. In many of our LS FGs when we asked a light-skinned person how they would react if they received an ancestry test that revealed that their ancestry was 90 percent African or Black, their faith in the reliability of DNA data sometimes led them to consider it a possibility (as long as the correct methods had been followed), even if unlikely. The question itself forced them to nuance a simple genetic determinism at the individual level and many LS people deployed genetic arguments about recessive genes and gene expression to explain the counter-intuitive:Irrespective of the economic or educational status of our participants, latency and manifestation were seen as the mechanisms, mostly framed as recessive or dominant genetic traits, that explained discrepancies between what we see with the naked eye and what is uncovered by the scientific gaze. Narratives of the ‘revelation’ of genetic truth and its ‘domestication’ by other factors were often framed in the idioms of genetic-phenotypic causation and genetic dormancy.In general, HS people explicitly distanced themselves from interpretations that in any way explained identities and behaviours through genetics. For them, behaviours and dispositions were a question of political position and cultural differences – which could however entail the naturalization of inequality – and they were rarely seen as an innate characteristic of people or a result of biological factors.ancestría – were incorporated into knowledge of family history and self. The indeterminacy of DNA at the individual scale of resolution allowed people to use it in very varied ways, which included both underwriting racial (and sometimes racist) determinism and challenging racist hierarchies.However, a key pattern that emerged from the LATINA groups – and indeed many other FGs, including the humanities ones – was that people selectively and strategically used ideas about genetic ancestry to reinforce ideas and agendas that they already held, often in relation to person and family. New objects and categories – such as genetic mestizaje, to analyse and measure it: ‘I came here to know where I come from, to know what my origins are. I come from a very mixed family’ (FG-LATINA C). Others approached the project looking for something more specific in their family history. As one person said: ‘I want to know if I am a pure López’ (FG-LATINA B). Likewise, an amateur genealogist participant said: ‘this test will show and prove our genealogical connection with Captain Velázquez … a founding father of Antioquia, and our great, great, great grandfather’ . For the latter two people, DNA could underwrite purity, rather than explain mixture.Some of the participants in the LATINA project came to it in exploratory mode, to dig into their own A few thought genetics could help steer a future that was under threat of racial contamination or degeneration:LATINA participant:I feel this can tell us all who we have been and where we are going.ESM:How would you do that?LATINA participant:You know, like if we have certain black, indigenous or white genes, and then we, at the personal and collective level, can think if we have the necessary things to progress. mestizaje as a process of progressive whitening Many of our informants imagined that the test results could be used by some people in an assertion of racial superiority:In the context of Paisa politics of belonging, genetic ancestry testing, rather than being an enterprise to debunk racism, as many LATINA organizers hoped, was seen by many participants as a proof of origin very much aligned with popular ideas of Paisas as proud of their origins, ethnocentric and possibly racist.These strategic uses of DNA were not confined to the LS people. Despite generally eschewing genetic determinism, some HS people deployed genetic knowledge for specific political purposes. A few people wanted to use genetic knowledge for subversive purposes: ‘I want LATINA to show them we all come from Africa, this test should be done to the many racists around, so they know they are also African’ . In another case, genetics was invoked when a respondent felt that her appearance did not match her sense of identity. This White member of a group of Afro-Colombian activists in Bogotá went to great lengths to explain how her spiritual and cultural affinities made her feel deeply identified with her Black colleagues. She not only emphasized her political and social connections, which she considered the main reasons for her participation in the group, but also insisted that her affinity was in part borne of her knowledge of various African or Black ancestors in her family, and the fact that ‘we all come from Africa’ (FG-Afro-Colombian).I would ask for a second analysis … if it comes with the same percentages I will start researching if such thing is possible. There would be a great question – if I have those percentages, then why I am like this? And then, I would laugh at myself, burst into tears and I would think, this is not fucking possible … I would change my type of friends, because one is accepted in many places, because one is like this . Normally if we find black people then we would beat them … imagine the change. … [After a moment of silence] I would have all these doubts, but I will still choose what I am in the moment, what I am, I will choose my beliefs, so I want to believe I am white, so be it – even though there is this contradiction. I would not choose the test … it might be the case that the numbers are scientific and objective, but for me my beliefs are more important than the numbers.The hypothetical idea that a person might possess very high percentages of any ancestry was accepted even by many Paisas, who said they personally would not marry Black or indigenous people, but still considered that, whatever the genetic result thrown at them, DNA should be considered the bottom line and the truth about their ancestral origins. In these cases, the ‘truth’ about ancestry would not necessarily change their attitudes about mixed marriages: genetic evidence was being strategically side-lined, rather than deployed. A clear example of this was a LATINA participant – a self-declared White supremacist – who estimated that he had 100 percent European genetic ancestry. When asked, ‘What would you do if the genetic test came back reporting you have 15% European ancestry and the rest divided between black and indigenous ancestry?’, he responded,Although this man initially resisted the hypothetical scenario, he eventually said that he would simply ignore the scenario’s uncomfortable (to him) genetic data. If genetic knowledge contradicted preferred narratives of belonging, a process of avoidance and denial began, as in this case and also that of several amateur genealogists to whom we spoke.mestizaje, which has produced a mainly mestizo population and culture, co-exists with a racialized geography of distinctive regions. This image was shared by all our FG participants, regardless of their background. However, the role genetic knowledge played in reinforcing this image and casting it into a genetic idiom turned out to be very uneven.The dominant image of Colombia is that of a country in which a long history of For some participants – located in the ‘certainty trough’  and who In contrast, HS people – humanities students and Afro-Colombian activists – treated genetics as a good deal less certain. Even though they might cede authority to genetics in terms of what it could reveal about individual ancestry, these people were more committed to alternative explanations of human variation, such as culture, which made the very categories used by genetic testing problematic. They resisted a racial idiom and profoundly challenged linking genetics to racial and regional difference at a collective level. For them, such links smacked of racism. Race had to be understood in terms of histories of power and oppression.However, even among the FG participants who adopted relatively mechanistic views of the relation between genetics, race and region, notions of genetic determinations and of ‘truths’ revealed by genetic ancestry tests were domesticated by the idea that a person was constituted by a variety of processes in which genetic structures were not the only factor. This view was to be expected among the HS people, who tended to be suspicious of genetic determinism – especially when linked discursively to race – and to attribute more importance to culture in the constitution of the person. But among the LS people we also found an important difference in the way genetics was seen to shape human diversity when they came to ponder individual bodies and genealogical connections, as opposed to collective categories of region, race and nation. While DNA was seen as a material vessel that had the power to shape not only physical appearances but also emotions and spiritual inclinations, its power was mediated by many other factors.Key here were ideas of dormant and expressive ancestries, which were used by many of our informants, often in the idiom of genetic science, to temper their mechanistic views. Latency and manifestation were used to account for multiple ways in which the individual was seen as fluid and not completely determined by genetics. Genetic dormancy and manifestation made it possible to re-interpret the ‘true’ racial-genetic source of each physical and psychological component. When the regional racial markers of belonging did not coincide with participants’ projects of self-fashioning, latency and manifestation allowed them to tap into the multiple possible connections of genetic ancestry and bring forth novel elements to define themselves. In this view, genetics was something like a set of components in a topological network, some of which become visible in our physical appearance or expressed in our likes and dislikes, while others remain submerged but may re-appear in different contexts. The view of genetic data as a malleable network of elements opened them up to strategic use – not only for the LS people, but also for the HS people. Despite their discomfort with genetic discourse, the latter groups might also use elements of genetic data to support certain agendas – such as the antiracist project of showing ‘racists’ that they too are Afro-descendants.In attempting to understand the role played by the data emerging from recent genomic science and circulating through different public spheres, we need to be attentive not only to specific groups who have a vested interest in genetics – such as patient groups and other such focuses of biosociality  and root