Linkage mapping of CVD risk traits in the isolated Norfolk Island population

To understand the underlying genetic architecture of cardiovascular disease (CVD) risk traits, we undertook a genome-wide linkage scan to identify CVD quantitative trait loci (QTLs) in 377 individuals from the Norfolk Island population. The central aim of this research focused on the utilization of a genetically and geographically isolated population of individuals from Norfolk Island for the purposes of variance component linkage analysis to identify QTLs involved in CVD risk traits. Substantial evidence supports the involvement of traits such as systolic and diastolic blood pressures, high-density lipoprotein-cholesterol, low-density lipoprotein-cholesterol, body mass index and triglycerides as important risk factors for CVD pathogenesis. In addition to the environmental influences of poor diet, reduced physical activity, increasing age, cigarette smoking and alcohol consumption, many studies have illustrated a strong involvement of genetic components in the CVD phenotype through family and twin studies. We undertook a genome scan using 400 markers spaced approximately 10 cM in 600 individuals from Norfolk Island. Genotype data was analyzed using the variance components methods of SOLAR. Our results gave a peak LOD score of 2.01 localizing to chromosome 1p36 for systolic blood pressure and replicated previously implicated loci for other CVD relevant QTLs.     

Heritability of interpack aggression in a wild pedigreed population of North American grey wolves

Aggression is a quantitative trait deeply entwined with individual fitness. Mapping the genomic architecture underlying such traits is complicated by complex inheritance patterns, social structure, pedigree information and gene pleiotropy. Here, we leveraged the pedigree of a reintroduced population of grey wolves (Canis lupus) in Yellowstone National Park, Wyoming, USA, to examine the heritability of and the genetic variation associated with aggression. Since their reintroduction, many ecological and behavioural aspects have been documented, providing unmatched records of aggressive behaviour across multiple generations of a wild population of wolves. Using a linear mixed model, a robust genetic relationship matrix, 12,288 single nucleotide polymorphisms (SNPs) and 111 wolves, we estimated the SNP‐based heritability of aggression to be 37% and an additional 14% of the phenotypic variation explained by shared environmental exposures. We identified 598 SNP genotypes from 425 grey wolves to resolve a consensus pedigree that was included in a heritability analysis of 141 individuals with SNP genotype, metadata and aggression data. The pedigree‐based heritability estimate for aggression is 14%, and an additional 16% of the phenotypic variation was explained by shared environmental exposures. We find strong effects of breeding status and relative pack size on aggression. Through an integrative approach, these results provide a framework for understanding the genetic architecture of a complex trait that influences individual fitness, with linkages to reproduction, in a social carnivore. Along with a few other studies, we show here the incredible utility of a pedigreed natural population for dissecting a complex, fitness‐related behavioural trait.     

Genomewide Linkage Analysis of Stature in Multiple Populations Reveals Several Regions with Evidence of Linkage to Adult Height

Genomewide linkage analysis has been extremely successful at identification of the genetic variation underlying single-gene disorders. However, linkage analysis has been less successful for common human diseases and other complex traits in which multiple genetic and environmental factors interact to influence disease risk. We hypothesized that a highly heritable complex trait, in which the contribution of environmental factors was relatively limited, might be more amenable to linkage analysis. We therefore chose to study stature (adult height), for which heritability is approximately 75%-90% (Phillips and Matheny 1990; Carmichael and McGue 1995; Preece 1996; Silventoinen et al. 2000). We reanalyzed genomewide scans from four populations for which genotype and height data were available, using a variance-components method implemented in GENEHUNTER 2.0 (Pratt et al. 2000). The populations consisted of 408 individuals in 58 families from the Botnia region of Finland, 753 individuals in 183 families from other parts of Finland, 746 individuals in 179 families from Southern Sweden, and 420 individuals in 63 families from the Saguenay-Lac-St.-Jean region of Quebec. Four regions showed evidence of linkage to stature: 6q24-25, multipoint LOD score 3.85 at marker D6S1007 in Botnia (genomewide P<.06), 7q31.3-36 (LOD 3.40 at marker D7S2195 in Sweden, P<.02), 12p11.2-q14 (LOD 3.35 at markers D12S10990-D12S398 in Finland, P<.05) and 13q32-33 (LOD 3.56 at markers D13S779-D13S797 in Finland, P<.05). In a companion article (Perola et al. 2001 [in this issue]), strong supporting evidence is obtained for linkage to the region on chromosome 7. These studies suggest that highly heritable complex traits such as stature may be genetically tractable and provide insight into the genetic architecture of complex traits.     

Geographic variation in cardiovascular inflammation among healthy women in the Women's Health Study

Background

Geographic variation in traditional cardiovascular disease (CVD) risk factors has been observed among women in the US. It is not known whether state-level variation in cardiovascular inflammation exists or could be explained by traditional clinical risk factors and behavioral lifestyle factors.

Methods and Results

We used multilevel linear regression to estimate state-level variation in inflammatory biomarker patterns adjusted for clinical and lifestyle characteristics among 26,029 women free of CVD. Participants derived from the Women''s Health Study, a national cohort of healthy middle-aged and older women. Inflammatory biomarker patterns (plasma levels of high-sensitivity C-reactive protein (hsCRP), soluble intercellular adhesion molecule-1 (sICAM-1), and fibrinogen) were compared to state-level patterns of traditional CVD risk factors and global risk scores. We found that all three inflammatory biomarkers exhibited significant state-level variation including hsCRP (lowest vs. highest state median 1.3 mg/L vs. 2.7 mg/L, unadjusted random effect estimate 1^st to 99^th percentile range for log hsCRP 0.52, p<.001), sICAM-1 (325 ng/ml vs. 366ng/ml, unadjusted random effect estimate 1^st to 99^th percentile range 0.44, p<.001), and fibrinogen (322 mg/dL vs. 367 mg/dL, unadjusted random effect estimate 1^st to 99^th percentile range 0.41, p = .001). Neither demographic, clinical or lifestyle characteristics explained away state-level effects in biomarker patterns. Southern and Appalachian states (Arkansas, West Virginia) had the highest inflammatory biomarker values. Regional geographic patterns of traditional CVD risk factors and risk scores did not completely overlap with biomarkers of inflammation.

Conclusions

There is state-level geographic variation in inflammatory biomarkers among otherwise healthy women that cannot be completely attributed to traditional clinical risk factors or lifestyle characteristics. Future research should aim to identify additional factors that may explain geographic variation in biomarkers of inflammation among healthy women.     

Sex-specific genetic architecture of human fatness in Chinese: the SAPPHIRe Study

To dissect the genetic architecture of sexual dimorphism in obesity-related traits, we evaluated the sex–genotype interaction, sex-specific heritability and genome-wide linkages for seven measurements related to obesity. A total of 1,365 non-diabetic Chinese subjects from the family study of the Stanford Asia–Pacific Program of Hypertension and Insulin Resistance were used to search for quantitative trait loci (QTLs) responsible for the obesity-related traits. Pleiotropy and co-incidence effects from the QTLs were also examined using the bivariate linkage approach. We found that sex-specific differences in heritability and the genotype–sex interaction effects were substantially significant for most of these traits. Several QTLs with strong linkage evidence were identified after incorporating genotype by sex (G × S) interactions into the linkage mapping, including one QTL for hip circumference [maximum LOD score (MLS) = 4.22, empirical p = 0.000033] and two QTLs: for BMI on chromosome 12q with MLS 3.37 (empirical p = 0.0043) and 3.10 (empirical p = 0.0054). Sex-specific analyses demonstrated that these linkage signals all resulted from females rather than males. Most of these QTLs for obesity-related traits replicated the findings in other ethnic groups. Bivariate linkage analyses showed several obesity traits were influenced by a common set of QTLs. All regions with linkage signals were observed in one gender, but not in the whole sample, suggesting the genetic architecture of obesity-related traits does differ by gender. These findings are useful for further identification of the liability genes for these phenotypes through candidate genes or genome-wide association analysis.     

A genome scan for quantitative trait loci in a wild population of red deer (Cervus elaphus)

Recent empirical evidence indicates that although fitness and fitness components tend to have low heritability in natural populations, they may nonetheless have relatively large components of additive genetic variance. The molecular basis of additive genetic variation has been investigated in model organisms but never in the wild. In this article we describe an attempt to map quantitative trait loci (QTL) for birth weight (a trait positively associated with overall fitness) in an unmanipulated, wild population of red deer (Cervus elaphus). Two approaches were used: interval mapping by linear regression within half-sib families and a variance components analysis of a six-generation pedigree of >350 animals. Evidence for segregating QTL was found on three linkage groups, one of which was significant at the genome-wide suggestive linkage threshold. To our knowledge this is the first time that a QTL for any trait has been mapped in a wild mammal population. It is hoped that this study will stimulate further investigations of the genetic architecture of fitness traits in the wild.     

Disease and Polygenic Architecture: Avoid Trio Design and Appropriately Account for Unscreened Control Subjects for Common Disease

Genome-wide association studies (GWASs) are an optimal design for discovery of disease risk loci for diseases whose underlying genetic architecture includes many common causal loci of small effect (a polygenic architecture). We consider two designs that deserve careful consideration if the true underlying genetic architecture of the trait is polygenic: parent-offspring trios and unscreened control subjects. We assess these designs in terms of quantification of the total contribution of genome-wide genetic markers to disease risk (SNP heritability) and power to detect an associated risk allele. First, we show that trio designs should be avoided when: (1) the disease has a lifetime risk > 1%; (2) trio probands are ascertained from families with more than one affected sibling under which scenario the SNP heritability can drop by more than 50% and power can drop as much as from 0.9 to 0.15 for a sample of 20,000 subjects; or (3) assortative mating occurs (spouse correlation of the underlying liability to the disorder), which decreases the SNP heritability but not the power to detect a single locus in the trio design. Some studies use unscreened rather than screened control subjects because these can be easier to collect; we show that the estimated SNP heritability should then be scaled by dividing by (1 − K × u)² for disorders with population prevalence K and proportion of unscreened control subjects u. When omitting to scale appropriately, the SNP heritability of, for example, major depressive disorder (K = 0.15) would be underestimated by 28% when none of the control subjects are screened.     

Age-stratified heritability estimation in the Framingham Heart Study families

The Framingham Heart Study provides a unique source of longitudinal family data related to CVD risk factors. Age-stratified heritability estimates were obtained over three age groups (31-49 years, 50-60 years, and 61-79 years), reflecting the longitudinal nature of the data, for four quantitative traits. Age-adjusted heritability estimates were obtained at a single common time point for the same four quantitative traits. The importance of these groups is that they consist of the same individuals. The highest age-stratified heritability estimate (h2 = 0.88 (+/- 0.06)) was for height in the model adjusting for gender over all three age groups. SBP gave the lowest heritability estimate (h2 = 0.15 (+/- 0.11)) for the 70 age group in the model adjusting for gender, height, BMI, smoker, and drinker. BMI had slightly higher estimates (h2 = 0.64 (+/- 0.11)) in the 40 age group than previously published. The highest age-adjusted heritability estimate (h2 = 0.90 (+/- 0.06)) was for height in the model adjusting for gender. SBP gave the lowest heritability estimate (h2 = 0.38 (+/- 0.09)) for unadjusted model. These results indicate that some common, complex traits may vary little in their genetic architecture over time and suggest that a common set of genes may be contributing to observed variation for these longitudinally collected phenotypes.     

Targeted quantitation of CVD-linked plasma proteins for biomarker verification and validation

Despite significant advances in treatment, cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in developed and developing countries. Judicious monitoring of common risk factors has been unable to control this global epidemic, necessitating novel biomarkers for improved screening and earlier disease detection and management. Although numerous plasma proteins have been associated with CVD, only a few of these potential biomarkers have been validated for clinical use. Here we review the quantitative proteomic methods used to verify and validate new biomarker candidates in human plasma. These methods center on a bottom-up approach involving multiple or selected reaction monitoring, for targeted detection, with stable isotope-labeled standards, for peptide normalization. Also included are a discussion of future strategies for improved CVD protein biomarker verification and validation, recommendations for method translation to the clinic, and future projections for protein biomarker research.     

Investigating the genetic architecture of conditional strategies using the environmental threshold model

The threshold expression of dichotomous phenotypes that are environmentally cued or induced comprise the vast majority of phenotypic dimorphisms in colour, morphology, behaviour and life history. Modelled as conditional strategies under the framework of evolutionary game theory, the quantitative genetic basis of these traits is a challenge to estimate. The challenge exists firstly because the phenotypic expression of the trait is dichotomous and secondly because the apparent environmental cue is separate from the biological signal pathway that induces the switch between phenotypes. It is the cryptic variation underlying the translation of cue to phenotype that we address here. With a ‘half-sib common environment’ and a ‘family-level split environment’ experiment, we examine the environmental and genetic influences that underlie male dimorphism in the earwig Forficula auricularia. From the conceptual framework of the latent environmental threshold (LET) model, we use pedigree information to dissect the genetic architecture of the threshold expression of forceps length. We investigate for the first time the strength of the correlation between observable and cryptic ‘proximate’ cues. Furthermore, in support of the environmental threshold model, we found no evidence for a genetic correlation between cue and the threshold between phenotypes. Our results show strong correlations between observable and proximate cues and less genetic variation for thresholds than previous studies have suggested. We discuss the importance of generating better estimates of the genetic variation for thresholds when investigating the genetic architecture and heritability of threshold traits. By investigating genetic architecture by means of the LET model, our study supports several key evolutionary ideas related to conditional strategies and improves our understanding of environmentally cued decisions.     

Environmental quality and evolutionary potential: lessons from wild populations

An essential requirement to determine a population's potential for evolutionary change is to quantify the amount of genetic variability expressed for traits under selection. Early investigations in laboratory conditions showed that the magnitude of the genetic and environmental components of phenotypic variation can change with environmental conditions. However, there is no consensus as to how the expression of genetic variation is sensitive to different environmental conditions. Recently, the study of quantitative genetics in the wild has been revitalized by new pedigree analyses based on restricted maximum likelihood, resulting in a number of studies investigating these questions in wild populations. Experimental manipulation of environmental quality in the wild, as well as the use of naturally occurring favourable or stressful environments, has broadened the treatment of different taxa and traits. Here, we conduct a meta-analysis on recent studies comparing heritability in favourable versus unfavourable conditions in non-domestic and non-laboratory animals. The results provide evidence for increased heritability in more favourable conditions, significantly so for morphometric traits but not for traits more closely related to fitness. We discuss how these results are explained by underlying changes in variance components, and how they represent a major step in our understanding of evolutionary processes in wild populations. We also show how these trends contrast with the prevailing view resulting mainly from laboratory experiments on Drosophila. Finally, we underline the importance of taking into account the environmental variation in models predicting quantitative trait evolution.     

Linkage and association analyses identify a candidate region for apoB level on chromosome 4q32.3 in FCHL families

Familial combined hyperlipidemia (FCHL) is a complex trait leading to cardiovascular disease (CVD) risk. Elevated levels and size of apolipoprotein B (apoB) and low-density lipoprotein (LDL) are associated with FCHL, which is genetically heterogeneous and is likely caused by rare variants. We carried out a linkage-based genome scan of four large FCHL pedigrees for apoB level that is independent of LDL: apoB level that is adjusted for LDL level and size. Follow-up included SNP genotyping in the region with the strongest evidence of linkage. Several regions with the evidence of linkage in individual pedigrees support the rare variant model. Evidence of linkage was strongest on chromosome 4q, with multipoint analysis in one pedigree giving LOD = 3.1 with a parametric model, and a log Bayes Factor = 1.5 from a Bayesian oligogenic approach. Of the 293 SNPs spanning the implicated region on 4q, rs6829588 completely explained the evidence of linkage. This SNP accounted for 39% of the apoB phenotypic variance, with heterozygotes for this SNP having a trait value that was ~30% higher than that of the high-frequency homozygote, thus identifying and considerably refining a strong candidate region. These results illustrate the advantage of using large pedigrees in the search for rare variants: reduced genetic heterogeneity within single pedigrees coupled with the large number of individuals segregating otherwise-rare single variants leads to high power to implicate such variants.     

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene‐mapping approach

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small‐effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine‐spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL‐mapping approaches based on a de‐biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL‐mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single‐locus analyses of an F₂ interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1–6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small‐effect loci. Apart from suggesting moderately heritable (h² ≈ 0.15–0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL‐mapping approach developed here has distinctive advantages over the traditional QTL‐mapping methods in analyses of dense marker panels.     

Heritability of cardiovascular and personality traits in 6,148 Sardinians

In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14–102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits.     

Genetic variation in biomass traits among 20 diverse rice varieties

Biofuels provide a promising route of producing energy while reducing reliance on petroleum. Developing sustainable liquid fuel production from cellulosic feedstock is a major challenge and will require significant breeding efforts to maximize plant biomass production. Our approach to elucidating genes and genetic pathways that can be targeted for improving biomass production is to exploit the combination of genomic tools and genetic diversity in rice (Oryza sativa). In this study, we analyzed a diverse set of 20 recently resequenced rice varieties for variation in biomass traits at several different developmental stages. The traits included plant size and architecture, aboveground biomass, and underlying physiological processes. We found significant genetic variation among the 20 lines in all morphological and physiological traits. Although heritability estimates were significant for all traits, heritabilities were higher in traits relating to plant size and architecture than for physiological traits. Trait variation was largely explained by variety and breeding history (advanced versus landrace) but not by varietal groupings (indica, japonica, and aus). In the context of cellulosic biofuels development, cell wall composition varied significantly among varieties. Surprisingly, photosynthetic rates among the varieties were inversely correlated with biomass accumulation. Examining these data in an evolutionary context reveals that rice varieties have achieved high biomass production via independent developmental and physiological pathways, suggesting that there are multiple targets for biomass improvement. Future efforts to identify loci and networks underlying this functional variation will facilitate the improvement of biomass traits in other grasses being developed as energy crops.     

Testing a ‘genes‐to‐ecosystems’ approach to understanding aquatic–terrestrial linkages

A ‘genes‐to‐ecosystems’ approach has been proposed as a novel avenue for integrating the consequences of intraspecific genetic variation with the underlying genetic architecture of a species to shed light on the relationships among hierarchies of ecological organization (genes → individuals → communities → ecosystems). However, attempts to identify genes with major effect on the structure of communities and/or ecosystem processes have been limited and a comprehensive test of this approach has yet to emerge. Here, we present an interdisciplinary field study that integrated a common garden containing different genotypes of a dominant, riparian tree, Populus trichocarpa, and aquatic mesocosms to determine how intraspecific variation in leaf litter alters both terrestrial and aquatic communities and ecosystem functioning. Moreover, we incorporate data from extensive trait screening and genome‐wide association studies estimating the heritability and genes associated with litter characteristics. We found that tree genotypes varied considerably in the quality and production of leaf litter, which contributed to variation in phytoplankton abundances, as well as nutrient dynamics and light availability in aquatic mesocosms. These ‘after‐life’ effects of litter from different genotypes were comparable to the responses of terrestrial communities associated with the living foliage. We found that multiple litter traits corresponding with aquatic community and ecosystem responses differed in their heritability. Moreover, the underlying genetic architecture of these traits was complex, and many genes contributed only a small proportion to phenotypic variation. Our results provide further evidence that genetic variation is a key component of aquatic–terrestrial linkages, but challenge the ability to predict community or ecosystem responses based on the actions of one or a few genes.     

Heritable variation in host tolerance and resistance inferred from a wild host–parasite system

Hosts have evolved two distinct defence strategies against parasites: resistance (which prevents infection or limit parasite growth) and tolerance (which alleviates the fitness consequences of infection). However, heritable variation in resistance and tolerance and the genetic correlation between these two traits have rarely been characterized in wild host populations. Here, we estimate these parameters for both traits in Leuciscus burdigalensis, a freshwater fish parasitized by Tracheliastes polycolpus. We used a genetic database to construct a full-sib pedigree in a wild L. burdigalensis population. We then used univariate animal models to estimate inclusive heritability (i.e. all forms of genetic and non-genetic inheritance) in resistance and tolerance. Finally, we assessed the genetic correlation between these two traits using a bivariate animal model. We found significant heritability for resistance (H = 17.6%; 95% CI: 7.2–32.2%) and tolerance (H = 18.8%; 95% CI: 4.4–36.1%), whereas we found no evidence for the existence of a genetic correlation between these traits. Furthermore, we confirm that resistance and tolerance are strongly affected by environmental effects. Our results demonstrate that (i) heritable variation exists for parasite resistance and tolerance in wild host populations, and (ii) these traits can evolve independently in populations.     

Genetic,epigenetic, and gene-by-diet interaction effects underlie variation in serum lipids in a LG/J×SM/J murine model

Variation in serum cholesterol, free-fatty acids, and triglycerides is associated with cardiovascular disease (CVD) risk factors. There is great interest in characterizing the underlying genetic architecture of these risk factors, because they vary greatly within and among human populations and between the sexes. We present results of a genome-wide scan for quantitative trait loci (QTL) affecting serum cholesterol, free-fatty acids, and triglycerides in an F₁₆ advanced intercross line of LG/J and SM/J (Wustl:LG,SM-G16). Half of the population was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. Here we examine genetic, environmental, and genetic-by-environmental interactions of QTL overlapping previously identified loci associated with CVD risk factors, and we add to the serum lipid QTL landscape by identifying new loci.     

Genetic and environmental variations in quantitative characters in fishes: a comparative analysis of monoclonal triploid and bisexual tetraploid spined loaches (<Emphasis Type="Italic">Cobitis</Emphasis>, Cobitidae)

The heritability estimates of 25 external morphometric characters and 23 craniometric indices are obtained by use of variances in monoclonal all-female triploids and bisexual tetraploids of spined loaches (genus Cobitis, Cobitidae) collected from the same breeding biotope. Most of studied traits demonstrate low heritability confirming previous conclusion on the similarity between external morphometric characters and craniological indices in relative effects of genetic and environmental components in their total phenotypic variation. Low heritability estimates in most of external morphological traits correspond to their low diagnostic value in Cobitis species. As a whole, in spite of certain deviations, studies on clonal forms do not refute the concept on higher heritability estimates in diagnostically significant traits in comparison with traits without diagnostic values in the same taxonomic group. Low heritability in most morphometric traits more probably is resulted from their low additive genetic variation caused by strong selection of evolutionary developed specific body shape in spined loaches, because strong selection should reduce the genetic variance in body proportions to minimal size. Sex differences observed in heritability estimates should be interpreted as a result of linkage of several additive genes controlling these traits to sex chromosomes. A few characters demonstrating high heritability estimates up to 0.492–0.580 are of great interest for taxonomic and phylogenetic studies in genus Cobitis and related taxa.