Identification, replication, and fine-mapping of Loci associated with adult height in individuals of african ancestry

Association of ZBTB38 gene polymorphism (rs724016) with height and fetal hemoglobin in individuals with sickle cell anemia

Objectives

Our study evaluated the association of the polymorphism rs724016 in the ZBTB38 gene, previously associated with height in other populations, with predictors of height, clinical outcomes, and laboratory parameters in sickle cell anemia (SCA).

Methods

Cross-sectional study with individuals with SCA and aged between 3 and 20 years. Clinical, laboratory, molecular, and bone age (BA) data were evaluated. Levels of IGF-1 and IGFBP-3 were adjusted for BA, target height (TH) was calculated as the mean parental height standard deviation score (SDS), and predicted adult height (PAH) SDS was calculated using BA.

Results

We evaluated 80 individuals with SCA. The homozygous genotype of the G allele of rs724016 was associated with a lower height SDS (p < 0.001) and, in a additive genetic model, was negatively associated with HbF levels (p = 0.016). Lower adjusted IGF-1 levels were associated with co-inheritance of alpha-thalassemia and with the absence of HU therapy. Elevated HbF levels were associated with a lower deficit in adjusted growth potential (TH minus PAH).

Conclusion

Our analysis shows that SNP rs724016 in the ZBTB38 is associated with shorter height and lower HbF levels, an important modifier of SCA.

Elucidation of genetic determinants of dyslipidaemia using a global screening array for the early detection of coronary artery disease

Dyslipidemia is a major risk factor for the development of coronary artery disease (CAD). Understanding the genetic determinants of dyslipidemia can provide valuable information on the pathogenesis of CAD and aid in the development of early detection strategies. In this study, we used a Global Screening Array (GSA) to elucidate the genetic factors associated with dyslipidemia and their potential role in the prediction of CAD. We conducted a GSA-based association study in 265 subjects to identify the genetic loci associated with dyslipidemia traits using Multiple Linear Regression (MLR) and Logistic Regression (LR), Classification and Regression Tree (CART), and Manhattan plots. We identified an association between dyslipidemia and variants identified in genes such as JCAD, GLIS3, CD38, FN1, CELSR2, MTNR1B, GIPR, DYM, APOB, APOE, ADCY5. The MLR models explained 62%, 71%, and 81% of the variability in HDL, LDL, and triglycerides, respectively. The Area Under the Curve (AUC) values in the LR models of HDL, LDL, and triglycerides were 1.00, 0.94, and 0.95, respectively. CART models identified novel gene-gene interactions influencing the risk for dyslipidemia. To conclude, we have identified the association of 12 SNVs with dyslipidemia and demonstrated their clinical utility in four different models such as MLR, LR, CART, and Manhattan plots. The identified genetic variants and associated pathways shed light on the underlying biology of dyslipidemia and offer potential avenues for precision medicine strategies in the management of CAD.

Human height: a model common complex trait

CONTEXT

Like other complex phenotypes, human height reflects a combination of environmental and genetic factors, but is notable for being exceptionally easy to measure. Height has therefore been commonly used to make observations later generalised to other phenotypes though the appropriateness of such generalisations is not always considered.

OBJECTIVES

We aimed to assess height's suitability as a model for other complex phenotypes and review recent advances in height genetics with regard to their implications for complex phenotypes more broadly.

METHODS

We conducted a comprehensive literature search in PubMed and Google Scholar for articles relevant to the genetics of height and its comparatibility to other phenotypes.

RESULTS

Height is broadly similar to other phenotypes apart from its high heritability and ease of measurment. Recent genome-wide association studies (GWAS) have identified over 12,000 independent signals associated with height and saturated height's common single nucleotide polymorphism based heritability of height within a subset of the genome in individuals similar to European reference populations.

CONCLUSIONS

Given the similarity of height to other complex traits, the saturation of GWAS's ability to discover additional height-associated variants signals potential limitations to the omnigenic model of complex-phenotype inheritance, indicating the likely future power of polygenic scores and risk scores, and highlights the increasing need for large-scale variant-to-gene mapping efforts.

Constructs, Tape Measures, and Mercury

This is a Lewinian-field-theory approach to understanding the Graduate Record Examination (GRE) in the context of racism to contribute to the debate about whether graduate schools should remove GRE scores from admissions processes. Woo and colleagues (this issue) review the empirical literature on bias from a psychometric perspective. In this commentary, I challenge the definition of the underlying construct measured by the GRE and offer alternative definitions of what is measured. Next, drawing on an analogy from genome-wide association studies, I discuss how genomic models predicting height that are trained on data from European ancestral populations systematically underpredict the height of West Africans. Our access to data from tape measures, and their correlation with height, provide objective opportunities to audit our prediction. I discuss the implications of this when the criterion variable for validating the GRE is first-year grades. I then probe an analogy used by Woo and colleagues in which they assert that blaming the GRE for disparities in scores across groups is akin to blaming the thermometer for global warming. I describe racism as context for a field-theory approach to thinking about the limitations of this misguided analogy. Finally, I suggest pathways forward.

Local ancestry prediction with PyLAE

Summary

We developed PyLAE, a new tool for determining local ancestry along a genome using whole-genome sequencing data or high-density genotyping experiments. PyLAE can process an arbitrarily large number of ancestral populations (with or without an informative prior). Since PyLAE does not involve estimating many parameters, it can process thousands of genomes within a day. PyLAE can run on phased or unphased genomic data. We have shown how PyLAE can be applied to the identification of differentially enriched pathways between populations. The local ancestry approach results in higher enrichment scores compared to whole-genome approaches. We benchmarked PyLAE using the 1000 Genomes dataset, comparing the aggregated predictions with the global admixture results and the current gold standard program RFMix. Computational efficiency, minimal requirements for data pre-processing, straightforward presentation of results, and ease of installation make PyLAE a valuable tool to study admixed populations.

Availability and implementation

The source code and installation manual are available at https://github.com/smetam/pylae.

Bench Research Informed by GWAS Results

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Allele frequency differentiation at height-associated SNPs among continental human populations

Methods to detect polygenic adaptation have recently been shown to be sensitive to uncorrected stratification in GWAS, thereby casting doubts on whether polygenic adaptation is prevalent among humans. Consistent with a signal of adaptation at human height loci, the mean F_ST among African, East Asian, and European populations was shown to be significantly higher at height-associated SNPs than that at non-associated SNPs. This conclusion was reached, however, using height-associated SNPs ascertained from a GWAS design impacted by residual confounding due to uncorrected stratification. Specifically, we show here that the estimated effect sizes are significantly correlated with population structure across continents, potentially explaining the elevated differentiation previously reported. We alleviated these concerns of confounding by ascertaining height-associated SNPs from two biobank GWAS (UK Biobank, UKB, and Biobank Japan, BBJ), where measures to control for confounding in GWAS are more effective. Consistent with a global signature of polygenic adaptation, we found that compared to non-associated SNPs, frequencies of height-associated SNPs are indeed significantly more differentiated among continental populations from both the 1000 Genomes Project (p = 0.0012 for UKB and p = 0.0265 for BBJ), and the Human Genome Diversity Project (p = 0.0225 for UKB and p = 0.0032 for BBJ). However, we found no significant difference among continental populations in polygenic height scores. Through simulations, we found that polygenic score-based statistics could lose power in detecting polygenic adaptation in presence of independent converging selections, thereby potentially explaining the inconsistent results based on F_ST and polygenic scores.

Associations between genetic loci related to lean mass and body composition in type 2 diabetes

Aim

Several genetic loci related to lean mass have been identified in healthy individuals by genome‐wide association studies; however, the contribution of these loci to body composition in type 2 diabetes remains to be investigated. Here, we aimed to clarify the genetic determinants of body composition in individuals with type 2 diabetes.

Methods

A total of 176 Japanese outpatients (70 women and 106 men) with type 2 diabetes were studied using a cross‐sectional design. Body composition was measured using bioimpedance analysis with a commercially available device (InBody770). Single‐nucleotide polymorphisms in IRS1 (rs2943656), HSD17B11 (rs9991501), VCAN (rs2287926), ADAMTSL3 (rs4842924) and FTO (rs9936385) were evaluated by genotyping. The contributions of single‐nucleotide polymorphisms to body composition were examined, considering known clinical determinants.

Results

Sex, body composition and age were identified as clinical predictors. IRS1 rs2934656 was identified as an independent predictor of skeletal muscle mass (β = 0.11, P = 0.026), and ADAMTSL3 rs4842924 was an independent predictor of body fat mass (β = 0.15, P = 0.0095) and appendicular lean mass (β = −0.13, P = 0.017).

Conclusions

The findings clarified the contribution of genetic factors – IRS1 and ADAMTSL3 – to interindividual variation in body composition, independent of clinical factors, in type 2 diabetes patients. These data will contribute to the establishment of effective methods for the prediction, prevention, and intervention of sarcopenia and frailty in diabetes patients. Geriatr Gerontol Int 2021; 21: 932–938.

A Genome-Wide Association Study of Novel Genetic Variants Associated With Anthropometric Traits in Koreans

Most previous genome-wide association studies (GWAS) have identified genetic variants associated with anthropometric traits. However, most of the evidence were reported in European populations. Anthropometric traits such as height and body fat distribution are significantly affected by gender and genetic factors. Here we performed GWAS involving 64,193 Koreans to identify the genetic factors associated with anthropometric phenotypes including height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip ratio. We found nine novel single-nucleotide polymorphisms (SNPs) and 59 independent genetic signals in genomic regions that were reported previously. Of the 19 SNPs reported previously, eight genetic variants at RP11-513I15.6 and one genetic variant at the RP11-977G19.10 region and six Asian-specific genetic variants were newly found. We compared our findings with those of previous studies in other populations. Five overlapping genetic regions (PAN2, ANKRD52, RNF41, HGMA1, and C6orf106) had been reported previously but none of the SNPs were independently identified in the current study. Seven of the nine newly found novel loci associated with height in women revealed a statistically significant skeletal expression of quantitative trait loci. Our study provides additional insight into the genetic effects of anthropometric phenotypes in East Asians.

Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

Population-Matched Transcriptome Prediction Increases TWAS Discovery and Replication Rate

Most genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) focus on European populations; however, these results cannot always be accurately applied to non-European populations due to genetic architecture differences. Using GWAS summary statistics in the Population Architecture using Genomics and Epidemiology study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we perform TWAS to determine gene-trait associations. We compared results using three transcriptome prediction models derived from Multi-Ethnic Study of Atherosclerosis populations: the African American and Hispanic/Latino (AFHI) model, the European (EUR) model, and the African American, Hispanic/Latino, and European (ALL) model. We identified 240 unique significant trait-associated genes. We found more significant, colocalized genes that replicate in larger cohorts when applying the AFHI model than the EUR or ALL model. Thus, TWAS with population-matched transcriptome models have more power for discovery and replication, demonstrating the need for more transcriptome studies in diverse populations.

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TWAS mechanistically extends GWAS findings in diverse populations

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Population-matched transcriptome models detect more replicable associations

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Colocalization shows GWAS variants likely act through gene expression regulation

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More GWAS and transcriptome modeling in diverse populations are needed

Polygenic Scores for Height in Admixed Populations

Polygenic risk scores (PRS) use the results of genome-wide association studies (GWAS) to predict quantitative phenotypes or disease risk at an individual level, and provide a potential route to the use of genetic data in personalized medical care. However, a major barrier to the use of PRS is that the majority of GWAS come from cohorts of European ancestry. The predictive power of PRS constructed from these studies is substantially lower in non-European ancestry cohorts, although the reasons for this are unclear. To address this question, we investigate the performance of PRS for height in cohorts with admixed African and European ancestry, allowing us to evaluate ancestry-related differences in PRS predictive accuracy while controlling for environment and cohort differences. We first show that the predictive accuracy of height PRS increases linearly with European ancestry and is partially explained by European ancestry segments of the admixed genomes. We show that recombination rate, differences in allele frequencies, and differences in marginal effect sizes across ancestries all contribute to the decrease in predictive power, but none of these effects explain the decrease on its own. Finally, we demonstrate that prediction for admixed individuals can be improved by using a linear combination of PRS that includes ancestry-specific effect sizes, although this approach is at present limited by the small size of non-European ancestry discovery cohorts.

A novel hypomorphic allele of Spag17 causes primary ciliary dyskinesia phenotypes in mice

Primary ciliary dyskinesia (PCD) is a human condition of dysfunctional motile cilia characterized by recurrent lung infection, infertility, organ laterality defects and partially penetrant hydrocephalus. We recovered a mouse mutant from a forward genetic screen that developed many of the hallmark phenotypes of PCD. Whole-exome sequencing identified this primary ciliary dyskinesia only (Pcdo) allele to be a nonsense mutation (c.5236A>T) in the Spag17 coding sequence creating a premature stop codon (K1746*). The Pcdo variant abolished several isoforms of SPAG17 in the Pcdo mutant testis but not in the brain. Our data indicate differential requirements for SPAG17 in different types of motile cilia. SPAG17 is essential for proper development of the sperm flagellum and is required for either development or stability of the C1 microtubule structure within the central pair apparatus of the respiratory motile cilia, but not the brain ependymal cilia. We identified changes in ependymal ciliary beating frequency, but these did not appear to alter lateral ventricle cerebrospinal fluid flow. Aqueductal stenosis resulted in significantly slower and abnormally directed cerebrospinal fluid flow, and we suggest that this is the root cause of the hydrocephalus. The Spag17Pcdo homozygous mutant mice are generally viable to adulthood but have a significantly shortened lifespan, with chronic morbidity. Our data indicate that the c.5236A>T Pcdo variant is a hypomorphic allele of Spag17 that causes phenotypes related to motile, but not primary, cilia. Spag17Pcdo is a useful new model for elucidating the molecular mechanisms underlying central pair PCD pathogenesis in the mouse.This article has an associated First Person interview with the first author of the paper.

Genetic Architecture Associated With Familial Short Stature

CONTEXT

Human height is an inheritable, polygenic trait under complex and multilocus genetic regulation. Familial short stature (FSS; also called genetic short stature) is the most common type of short stature and is insufficiently known.

OBJECTIVE

To investigate the FSS genetic profile and develop a polygenic risk predisposition score for FSS risk prediction.

DESIGN AND SETTING

The FSS participant group of Han Chinese ancestry was diagnosed by pediatric endocrinologists in Taiwan.

PATIENTS AND INTERVENTIONS

The genetic profiles of 1163 participants with FSS were identified by using a bootstrapping subsampling and genome-wide association studies (GWAS) method.

MAIN OUTCOME MEASURES

Genetic profile, polygenic risk predisposition score for risk prediction.

RESULTS

Ten novel genetic single nucleotide polymorphisms (SNPs) and 9 reported GWAS human height-related SNPs were identified for FSS risk. These 10 novel SNPs served as a polygenic risk predisposition score for FSS risk prediction (area under the curve: 0.940 in the testing group). This FSS polygenic risk predisposition score was also associated with the height reduction regression tendency in the general population.

CONCLUSION

A polygenic risk predisposition score composed of 10 genetic SNPs is useful for FSS risk prediction and the height reduction tendency. Thus, it might contribute to FSS risk in the Han Chinese population from Taiwan.

Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types

Natural selection and domestication have shaped modern horse populations, resulting in a vast range of phenotypically diverse breeds. Horse breeds are classified into three types (pony, light, and draft) generally based on their body type. Understanding the genetic basis of horse type variation and selective pressures related to the evolutionary trend can be particularly important for current selection strategies. Whole-genome sequences were generated for 14 pony and 32 light horses to investigate the genetic signatures of selection of the horse type in pony and light horses. In the overlapping extremes of the fixation index and nucleotide diversity results, we found novel genomic signatures of selective sweeps near key genes previously implicated in body measurements including C4ORF33, CRB1, CPN1, FAM13A, and FGF12 that may influence variation in pony and light horse types. This study contributes to a better understanding of the genetic background of differences between pony and light horse types.

Genetic and environmental influences on human height from infancy through adulthood at different levels of parental education

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju horse

The Jeju horse, indigenous to the Jeju Island in Korea may have originated from Mongolian horses. Adaptations to the local harsh environment have conferred Jeju horse with unique traits such as small-sized body, stocky head, and shorter limbs. These characteristics have not been studied previously at the genomic level. Therefore, we sequenced and compared the genome of 41 horses belonging to 6 breeds. We identified numerous breed-specific non-synonymous SNPs and loss-of-function mutants. Demographic and admixture analyses showed that, though Jeju horse is genetically the closest to the Mongolian breeds, its genetic ancestry is independent of that of the Mongolian breeds. Genome wide selection signature analysis revealed that genes such as LCORL, MSTN, HMGA2, ZFAT, LASP1, PDK4, and ACTN2, were positively selected in the Jeju horse. RNAseq analysis showed that several of these genes were also differentially expressed in Jeju horse compared to Thoroughbred horse. Comparative muscle fiber analysis showed that, the type I muscle fibre content was substantially higher in Jeju horse compared to Thoroughbred horse. Our results provide insights about the selection of complex phenotypic traits in the small-sized Jeju horse and the novel SNPs identified will aid in designing high-density SNP chip for studying other native horse breeds.

Complex Phenotypes: Mechanisms Underlying Variation in Human Stature

PURPOSE OF REVIEW

The goal of the review is to provide a comprehensive overview of the current understanding of the mechanisms underlying variation in human stature.

RECENT FINDINGS

Human height is an anthropometric trait that varies considerably within human populations as well as across the globe. Historically, much research focus was placed on understanding the biology of growth plate chondrocytes and how modifications to core chondrocyte proliferation and differentiation pathways potentially shaped height attainment in normal as well as pathological contexts. Recently, much progress has been made to improve our understanding regarding the mechanisms underlying the normal and pathological range of height variation within as well as between human populations, and today, it is understood to reflect complex interactions among a myriad of genetic, environmental, and evolutionary factors. Indeed, recent improvements in genetics (e.g., GWAS) and breakthroughs in functional genomics (e.g., whole exome sequencing, DNA methylation analysis, ATAC-sequencing, and CRISPR) have shed light on previously unknown pathways/mechanisms governing pathological and common height variation. Additionally, the use of an evolutionary perspective has also revealed important mechanisms that have shaped height variation across the planet. This review provides an overview of the current knowledge of the biological mechanisms underlying height variation by highlighting new research findings on skeletal growth control with an emphasis on previously unknown pathways/mechanisms influencing pathological and common height variation. In this context, this review also discusses how evolutionary forces likely shaped the genomic architecture of height across the globe.

Genome-wide association analysis of 95 549 individuals identifies novel loci and genes influencing optic disc morphology

Optic nerve head morphology is affected by several retinal diseases. We measured the vertical optic disc diameter (DD) of the UK Biobank (UKBB) cohort (N = 67 040) and performed the largest genome-wide association study (GWAS) of DD to date. We identified 81 loci (66 novel) for vertical DD. We then replicated the novel loci in International Glaucoma Genetic Consortium (IGGC, N = 22 504) and European Prospective Investigation into Cancer–Norfolk (N = 6005); in general the concordance in effect sizes was very high (correlation in effect size estimates 0.90): 44 of the 66 novel loci were significant at P &lt; 0.05, with 19 remaining significant after Bonferroni correction. We identified another 26 novel loci in the meta-analysis of UKBB and IGGC data. Gene-based analyses identified an additional 57 genes. Human ocular tissue gene expression analysis showed that most of the identified genes are enriched in optic nerve head tissue. Some of the identified loci exhibited pleiotropic effects with vertical cup-to-disc ratio, intraocular pressure, glaucoma and myopia. These results can enhance our understanding of the genetics of optic disc morphology and shed light on the genetic findings for other ophthalmic disorders such as glaucoma and other optic nerve diseases.

Dog10K: an international sequencing effort to advance studies of canine domestication, phenotypes and health

Dogs are the most phenotypically diverse mammalian species, and they possess more known heritable disorders than any other non-human mammal. Efforts to catalog and characterize genetic variation across well-chosen populations of canines are necessary to advance our understanding of their evolutionary history and genetic architecture. To date, no organized effort has been undertaken to sequence the world's canid populations. The Dog10K Consortium (http://www.dog10kgenomes.org) is an international collaboration of researchers from across the globe who will generate 20× whole genomes from 10 000 canids in 5 years. This effort will capture the genetic diversity that underlies the phenotypic and geographical variability of modern canids worldwide. Breeds, village dogs, niche populations and extended pedigrees are currently being sequenced, and de novo assemblies of multiple canids are being constructed. This unprecedented dataset will address the genetic underpinnings of domestication, breed formation, aging, behavior and morphological variation. More generally, this effort will advance our understanding of human and canine health.

Two Insertion/Deletion Variants within SPAG17 Gene Are Associated with Goat Body Measurement Traits

Simple Summary

Sperm-associated antigen 17 (SPAG17) is a reproduction and skeletal development related gene. This study aimed to identify crucial insertion-deletion (indel) variations, which influence the body measurement traits of goats. Two intronic indels (14 bp and 17 bp indels) were identified by sequencing. In Shaanbei white cashmere goat (SBWC), the different genotypes of the 14 bp indel were markedly associated with goat body height, chest width, body length, and chest depth. The genotypes of the 17 bp indel were significantly associated with body height and chest width. The different combined genotypes were significantly associated with body height and chest width of SBWC and ten traits of Hainan black goat. These results suggested that the 14 and 17 bp indels within SPAG17 can be used in goat growth related traits marker-assisted selection breeding, especially body height.

Abstract

Sperm-associated antigen 17 (SPAG17) gene encodes a multifunctional cytoplasmic protein, which influences not only reproduction but also skeletal development related body measurement traits, especially body height. Thus, this study aimed to identify crucial insertion-deletion (indel) variations, which influence the body measurement traits of goats in large goat populations (n = 1725). As a result, two intronic indels (14 bp and 17 bp indel) were identified by sequencing. For the two indel loci, the distributions of genotypes and alleles were significantly different between the Shaanbei white cashmere goat (SBWC) and the Hainan black goat (HNBG). In SBWC goats, the different genotypes of the 14 bp indel were markedly associated with goat body height, chest width, body length and chest depth. The genotypes of the 17 bp indel were significantly related to body height and chest width. At the two loci, for all seven analyzed traits of SBWC goat, the growth data of DD homozygotes were the worst, which means that the 14 bp insertion and the 17 bp deletion were beneficial and detrimental variations, respectively. Moreover, the combined genotypes were significantly related to body height and chest width of SBWC goats and ten traits of HNBG. These results suggested that the 14 and 17 bp indels within SPAG17 can be used in goat growth related traits marker-assisted selection breeding, especially body height.

Relationship of genetic determinants of height with cardiometabolic and pulmonary traits in the Hispanic Community Health Study/Study of Latinos

Background

Associations of adult height with cardiometabolic and pulmonary traits have been studied in majority European ancestry populations using Mendelian randomization and polygenic risk score (PRS) analysis. The standard PRS approach entails creating a PRS for height using variants identified in prior genome-wide association studies (GWAS). It is unclear how well the standard PRS approach performs in non-European populations and whether height-trait associations observed in Europeans are also observed in other populations.

Methods

In the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), we used: (i) the standard approach to create a PRS for height (PRS1) and (ii) a novel approach to optimize the selection of variants from previously established height association loci to better explain height in HCHS/SOL (PRS2). We also estimated the extent to which PRS-trait associations were independent or mediated by the PRS effect on height.

Results

In 7539 women and 5245 men, PRS1 and PRS2 explained 9 and 29% of the variance in measured height, respectively. Both PRS1 and PRS2 were associated with forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), FEV1/ FVC ratio, total cholesterol and 2-hour oral glucose-tolerance test insulin levels. Additionally, PRS2 was associated with estimated glomerular filtration rate and ankle brachial index. Both PRS1 and PRS2 had pleiotropic associations with FEV1/ FVC ratio in mediation analyses.

Conclusions

Associations of polygenic scores of height with measures of lung function and cholesterol were consistent with those observed in prior studies of majority European ancestry populations. Mediation analysis may augment standard PRS approaches to disentangle pleiotropic and mediated effects.

Analysis of a large dataset reveals haplotypes carrying putatively recessive lethal and semi-lethal alleles with pleiotropic effects on economically important traits in beef cattle

BACKGROUND

In livestock, deleterious recessive alleles can result in reduced economic performance of homozygous individuals in multiple ways, e.g. early embryonic death, death soon after birth, or semi-lethality with incomplete penetrance causing reduced viability. While death is an easy phenotype to score, reduced viability is not as easy to identify. However, it can sometimes be observed as reduced conception rates, longer calving intervals, or lower survival for live born animals.

METHODS

In this paper, we searched for haplotypes that carry putatively recessive lethal or semi-lethal alleles in 132,725 genotyped Irish beef cattle from five breeds: Aberdeen Angus, Charolais, Hereford, Limousin, and Simmental. We phased the genotypes in sliding windows along the genome and used five tests to identify haplotypes with absence of or reduced homozygosity. Then, we associated the identified haplotypes with 44,351 insemination records that indicated early embryonic death, and postnatal survival records. Finally, we assessed haplotype pleiotropy by estimating substitution effects on estimates of breeding value for 15 economically important traits in beef production.

RESULTS

We found support for one haplotype that carries a putatively recessive lethal (chromosome 16 in Simmental) and two haplotypes that carry semi-lethal alleles (chromosome 14 in Aberdeen Angus and chromosome 19 in Charolais), with population frequencies of 8.8, 15.2, and 14.4%, respectively. These three haplotypes showed pleiotropic effects on economically important traits for beef production. Their allele substitution effects are €2.30, €3.42, and €1.47 for the terminal index and €1.03, - €3.11, and - €0.88 for the replacement index, where the standard deviations for the terminal index are €22.52, €18.65, and €22.70 and for the replacement index they are €31.35, €29.82, and €35.79. We identified ZFAT as the candidate gene for semi-lethality in Aberdeen Angus, several candidate genes for the lethal Simmental haplotype, and no candidate genes for the semi-lethal Charolais haplotype.

CONCLUSIONS

We analysed genotype, reproduction, survival, and production data to detect haplotypes that carry putatively recessive lethal or semi-lethal alleles in Irish beef cattle and identified one lethal and two semi-lethal haplotypes, which have pleiotropic effects on economically important traits in beef production.

A genome scan for genes underlying adult body size differences between Central African hunter-gatherers and farmers

The evolutionary and biological bases of the Central African "pygmy" phenotype, a characteristic of rainforest hunter-gatherers defined by reduced body size compared with neighboring farmers, remain largely unknown. Here, we perform a joint investigation in Central African hunter-gatherers and farmers of adult standing height, sitting height, leg length, and body mass index (BMI), considering 358 hunter-gatherers and 169 farmers with genotypes for 153,798 SNPs. In addition to reduced standing heights, hunter-gatherers have shorter sitting heights and leg lengths and higher sitting/standing height ratios than farmers and lower BMI for males. Standing height, sitting height, and leg length are strongly correlated with inferred levels of farmer genetic ancestry, whereas BMI is only weakly correlated, perhaps reflecting greater contributions of non-genetic factors to body weight than to height. Single- and multi-marker association tests identify one region and eight genes associated with hunter-gatherer/farmer status, and 24 genes associated with the height-related traits. Many of these genes have putative functions consistent with roles in determining their associated traits and the pygmy phenotype, and they include three associated with standing height in non-Africans (PRKG1, DSCAM, MAGI2). We find evidence that European height-associated SNPs or variants in linkage disequilibrium with them contribute to standing- and sitting-height determination in Central Africans, but not to the differential status of hunter-gatherers and farmers. These findings provide new insights into the biological basis of the pygmy phenotype, and they highlight the potential of cross-population studies for exploring the genetic basis of phenotypes that vary naturally across populations.

Admixture mapping and fine-mapping of birth weight loci in the Black Women's Health Study

Several genome-wide association studies (GWAS) have identified genetic variants associated with birth weight. To date, however, most GWAS of birth weight have focused primarily on European ancestry samples even though prevalence of low birth weight is higher among African-Americans. We conducted admixture mapping using 2918 ancestral informative markers in 2596 participants of the Black Women's Health Study, with the goal of identifying novel genomic regions where local African ancestry is associated with birth weight. In addition, we performed a replication analysis of 11 previously identified index single nucleotide polymorphisms (SNPs), and fine-mapped those genetic loci to identify better or new genetic variants associated with birth weight in African-Americans. We found that high African ancestry at 12q14 was associated with low birth weight, and we identified multiple independent birth weight-lowering variants in this genomic region. We replicated the association of a previous GWAS SNP in ADRB1 and our fine-mapping efforts suggested the presence of new birth weight-associated variants in ADRB1, HMGA2, and SLC2A4. Further studies are needed to determine whether birth weight-associated loci can in part explain race-associated birth weight disparities.

Genome-wide association study identifies loci and candidate genes for internal organ weights in Simmental beef cattle

Cattle internal organs as accessible raw materials have a long history of being widely used in beef processing, feed and pharmaceutical industry. These traits not only are of economic interest to breeders, but they are intrinsically linked to many valuable traits, such as growth, health, and productivity. Using the Illumina Bovine HD 770K SNP array, we performed a genome-wide association study for heart weight, liver weight, spleen weight, lung weight, and kidney weight in 1,217 Simmental cattle. In our research, 38 significant single nucleotide polymorphisms (SNPs) ( P < 1.49 × 10−6) were identified for five internal organ weight traits. These SNPs are within or near 13 genes, and some of them have been reported previously, including NDUFAF4, LCORL, BT.94996, SLIT2, FAM184B, LAP3, BBS12, MECOM, CD300LF, HSD17B3, TLR4, MXI1, and MB21D2. In addition, we detected four haplotype blocks on BTA6 containing 18 significant SNPs associated with spleen weight. Our results offer worthy insights into understanding the genetic mechanisms of internal organs' development, with potential application in breeding programs of Simmental beef cattle.

Transethnic differences in GWAS signals: A simulation study

Genome-wide association studies (GWASs) have allowed researchers to identify thousands of single nucleotide polymorphisms (SNPs) and other variants associated with particular complex traits. Previous studies have reported differences in the strength and even the direction of GWAS signals across different populations. These differences could be due to a combination of (1) lack of power, (2) allele frequency differences, (3) linkage disequilibrium (LD) differences, and (4) true differences in causal variant effect sizes. To determine whether properties (1)-(3) on their own might be sufficient to explain the patterns previously noted in strong GWAS signals, we simulated case-control data of European, Asian and African ancestry, applying realistic allele frequencies and LD from 1000 Genomes data but enforcing equal causal effect sizes across populations. Much of the observed differences in strong GWAS signals could indeed be accounted for by allele frequency and LD differences, enhanced by the Euro-centric SNP bias and lower SNP coverage found in older GWAS panels. While we cannot rule out a role for true transethnic effect size differences, our results suggest that strong causal effects may be largely shared among human populations, motivating the use of transethnic data for fine-mapping.

Multiethnic polygenic risk scores improve risk prediction in diverse populations

Methods for genetic risk prediction have been widely investigated in recent years. However, most available training data involves European samples, and it is currently unclear how to accurately predict disease risk in other populations. Previous studies have used either training data from European samples in large sample size or training data from the target population in small sample size, but not both. Here, we introduce a multiethnic polygenic risk score that combines training data from European samples and training data from the target population. We applied this approach to predict type 2 diabetes (T2D) in a Latino cohort using both publicly available European summary statistics in large sample size (Neff  = 40k) and Latino training data in small sample size (Neff  = 8k). Here, we attained a >70% relative improvement in prediction accuracy (from R2  = 0.027 to 0.047) compared to methods that use only one source of training data, consistent with large relative improvements in simulations. We observed a systematically lower load of T2D risk alleles in Latino individuals with more European ancestry, which could be explained by polygenic selection in ancestral European and/or Native American populations. We predict T2D in a South Asian UK Biobank cohort using European (Neff  = 40k) and South Asian (Neff  = 16k) training data and attained a >70% relative improvement in prediction accuracy, and application to predict height in an African UK Biobank cohort using European (N = 113k) and African (N = 2k) training data attained a 30% relative improvement. Our work reduces the gap in polygenic risk prediction accuracy between European and non-European target populations.

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 × 10-8) or suggestively genome wide (p < 2.3 × 10-6). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass.Lean body mass is a highly heritable trait and is associated with various health conditions. Here, Kiel and colleagues perform a meta-analysis of genome-wide association studies for whole body lean body mass and find five novel genetic loci to be significantly associated.

Diversity and inclusion in genomic research: why the uneven progress?

Conducting genomic research in diverse populations has led to numerous advances in our understanding of human history, biology, and health disparities, in addition to discoveries of vital clinical significance. Conducting genomic research in diverse populations is also important in ensuring that the genomic revolution does not exacerbate health disparities by facilitating discoveries that will disproportionately benefit well-represented populations. Despite the general agreement on the need for genomic research in diverse populations in terms of equity and scientific progress, genomic research remains largely focused on populations of European descent. In this article, we describe the rationale for conducting genomic research in diverse populations by reviewing examples of advances facilitated by their inclusion. We also explore some of the factors that perpetuate the disproportionate attention on well-represented populations. Finally, we discuss ongoing efforts to ameliorate this continuing bias. Collaborative and intensive efforts at all levels of research, from the funding of studies to the publication of their findings, will be necessary to ensure that genomic research does not conserve historical inequalities or curtail the contribution that genomics could make to the health of all humanity.

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations

The vast majority of genome-wide association studies (GWASs) are performed in Europeans, and their transferability to other populations is dependent on many factors (e.g., linkage disequilibrium, allele frequencies, genetic architecture). As medical genomics studies become increasingly large and diverse, gaining insights into population history and consequently the transferability of disease risk measurement is critical. Here, we disentangle recent population history in the widely used 1000 Genomes Project reference panel, with an emphasis on populations underrepresented in medical studies. To examine the transferability of single-ancestry GWASs, we used published summary statistics to calculate polygenic risk scores for eight well-studied phenotypes. We identify directional inconsistencies in all scores; for example, height is predicted to decrease with genetic distance from Europeans, despite robust anthropological evidence that West Africans are as tall as Europeans on average. To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coalescent-based simulation framework considering effects of polygenicity, causal allele frequency divergence, and heritability. As expected, correlations between true and inferred risk are typically highest in the population from which summary statistics were derived. We demonstrate that scores inferred from European GWASs are biased by genetic drift in other populations even when choosing the same causal variants and that biases in any direction are possible and unpredictable. This work cautions that summarizing findings from large-scale GWASs may have limited portability to other populations using standard approaches and highlights the need for generalized risk prediction methods and the inclusion of more diverse individuals in medical genomics.

Association of gene coding variation and resting metabolic rate in a multi-ethnic sample of children and adults

Background

Resting metabolic rates (RMR) vary across individuals. Understanding the determinants of RMR could provide biological insight into obesity and its metabolic consequences such as type 2 diabetes and cardiovascular diseases.

Methods

The present study measured RMR using reference standard indirect calorimetry and evaluated genetic variations from an exome array in a sample of children and adults (N = 262) predominantly of African and European ancestry with a wide range of ages (10 – 67 years old) and body mass indices (BMI; 16.9 – 56.3 kg/m² for adults, 15.1 – 40.6 kg/m2 for children).

Results

Single variant analysis for RMR identified suggestive loci on chromosomes 15 (rs74010762, TRPM1, p-value = 2.7 × 10−6), 1 (rs2358728 and rs2358729, SH3D21, p-values < 5.8x10−5), 17 (AX-82990792, DHX33, 5.5 × 10−5) and 5 (rs115795863 and rs35433829, C5orf33 and RANBP3L, p-values < 8.2 × 10−5). To evaluate the effect of low frequency variations with RMR, we performed gene-based association tests. Our most significant locus was SH3D21 (p-value 2.01 × 10−4), which also contained suggestive results from single-variant analyses. A further investigation of all variants within the reported genes for all obesity-related loci from the GWAS catalog found nominal evidence for association of body mass index (BMI- kg/m²)-associated loci with RMR, with the most significant p-value at rs35433754 (TNKS, p-value = 0.0017).

Conclusions

These nominal associations were robust to adjustment for BMI. The most significant variants were also evaluated using phenome-wide association to evaluate pleiotropy, and genetically predicted gene expression using the summary statistics implicated loci related to in obesity and body composition. These results merit further examination in larger cohorts of children and adults.

Electronic supplementary material

The online version of this article (doi:10.1186/s40608-017-0145-5) contains supplementary material, which is available to authorized users.

Genetic and environmental influences on adult human height across birth cohorts from 1886 to 1994

Human height variation is determined by genetic and environmental factors, but it remains unclear whether their influences differ across birth-year cohorts. We conducted an individual-based pooled analysis of 40 twin cohorts including 143,390 complete twin pairs born 1886–1994. Although genetic variance showed a generally increasing trend across the birth-year cohorts, heritability estimates (0.69-0.84 in men and 0.53-0.78 in women) did not present any clear pattern of secular changes. Comparing geographic-cultural regions (Europe, North America and Australia, and East Asia), total height variance was greatest in North America and Australia and lowest in East Asia, but no clear pattern in the heritability estimates across the birth-year cohorts emerged. Our findings do not support the hypothesis that heritability of height is lower in populations with low living standards than in affluent populations, nor that heritability of height will increase within a population as living standards improve.

DOI:http://dx.doi.org/10.7554/eLife.20320.001

Mammalian axoneme central pair complex proteins: Broader roles revealed by gene knockout phenotypes

The axoneme genes, their encoded proteins, their functions and the structures they form are largely conserved across species. Much of our knowledge of the function and structure of axoneme proteins in cilia and flagella is derived from studies on model organisms like the green algae, Chlamydomonas reinhardtii. The core structure of cilia and flagella is the axoneme, which in most motile cilia and flagella contains a 9 + 2 configuration of microtubules. The two central microtubules are the scaffold of the central pair complex (CPC). Mutations that disrupt CPC genes in Chlamydomonas and other model organisms result in defects in assembly, stability and function of the axoneme, leading to flagellar motility defects. However, targeted mutations generated in mice in the orthologous CPC genes have revealed significant differences in phenotypes of mutants compared to Chlamydomonas. Here we review observations that support the concept of cell-type specific roles for the CPC genes in mice, and an expanded repertoire of functions for the products of these genes in cilia, including non-motile cilia, and other microtubule-associated cellular functions.

Association Study of GWAS-Derived Loci with Height in Brazilian Children: Importance of MAP3K3, MMP24 and IGF1R Polymorphisms for Height Variation

BACKGROUND/AIM

The single nucleotide polymorphisms (SNPs) rs2282978 (CDK6), rs2425019 (MMP24), rs8081612 (MAP3K3), rs2871865 (IGF1R) and rs3782415 (SOCS2) were among the SNPs most strongly associated with height in a meta-analysis of 47 genome-wide association studies (GWAS) involving 114,223 adults from six ethnic groups. The present study aimed to examine associations between these SNPs and height in Brazilian children.

METHODS

Cross-sectional heights of 1,008 healthy unrelated 4.4- to 9.7-year-old children were evaluated. All genotypes were determined by allele-specific polymerase chain reactions. Height standard deviation scores (SDS) were generated for this population and regressed on allele counts. Linear regressions were performed to estimate the effect of individual SNPs or a polygenic allelic score on height.

RESULTS

The T allele of rs8081612 (MAP3K3), the C allele of rs2871865 (IGF1R) and the G allele of rs2425019 (MMP24) were significantly associated with a 0.091-SDS greater height (95% CI 0.089-0.093, p = 0.001) by polygenic analysis. The mean height SDS difference between children with 2 'tall' alleles and children with 4 'tall' alleles was 0.24 SDS (95% CI 0.05-0.43, p = 0.01). The observed allelic effect is consistent with that found in previous GWAS.

CONCLUSIONS

Polymorphisms in MAP3K3, MMP24 and IGF1R act additively on height in children of an admixed population. These results demonstrate the importance of these loci for children's height.

Genetic and environmental influences on height from infancy to early adulthood: An individual-based pooled analysis of 45 twin cohorts

Height variation is known to be determined by both genetic and environmental factors, but a systematic description of how their influences differ by sex, age and global regions is lacking. We conducted an individual-based pooled analysis of 45 twin cohorts from 20 countries, including 180,520 paired measurements at ages 1-19 years. The proportion of height variation explained by shared environmental factors was greatest in early childhood, but these effects remained present until early adulthood. Accordingly, the relative genetic contribution increased with age and was greatest in adolescence (up to 0.83 in boys and 0.76 in girls). Comparing geographic-cultural regions (Europe, North-America and Australia, and East-Asia), genetic variance was greatest in North-America and Australia and lowest in East-Asia, but the relative proportion of genetic variation was roughly similar across these regions. Our findings provide further insights into height variation during childhood and adolescence in populations representing different ethnicities and exposed to different environments.

PLAG1 and NCAPG-LCORL in livestock

A recent progress on stature genetics has revealed simple genetic architecture in livestock animals in contrast to that in humans. PLAG1 and/or NCAPG‐LCORL, both of which are known as a locus for adult human height, have been detected for association with body weight/height in cattle and horses, and for selective sweep in dogs and pigs. The findings indicate a significant impact of these loci on mammalian growth or body size and usefulness of the natural variants for selective breeding. However, association with an unfavorable trait, such as late puberty or risk for a neuropathic disease, was also reported for the respective loci, indicating an importance to discriminate between causality and association. Here I review the recent findings on quantitative trait loci (QTL) for stature in livestock animals, mainly focusing on the PLAG1 and NCAPG‐LCORL loci. I also describe our recent efforts to identify the causative variation for the third major locus for carcass weight in Japanese Black cattle.

Methodological Considerations in Estimation of Phenotype Heritability Using Genome-Wide SNP Data, Illustrated by an Analysis of the Heritability of Height in a Large Sample of African Ancestry Adults

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.

Spag17 deficiency results in skeletal malformations and bone abnormalities

Height is the result of many growth and development processes. Most of the genes associated with height are known to play a role in skeletal development. Single-nucleotide polymorphisms in the SPAG17 gene have been associated with human height. However, it is not clear how this gene influences linear growth. Here we show that a targeted mutation in Spag17 leads to skeletal malformations. Hind limb length in mutants was significantly shorter than in wild-type mice. Studies revealed differences in maturation of femur and tibia suggesting alterations in limb patterning. Morphometric studies showed increased bone formation evidenced by increased trabecular bone area and the ratio of bone area to total area, leading to reductions in the ratio of marrow area/total area in the femur. Micro-CTs and von Kossa staining demonstrated increased mineral in the femur. Moreover, osteocalcin and osterix were more highly expressed in mutant mice than in wild-type mice femurs. These data suggest that femur bone shortening may be due to premature ossification. On the other hand, tibias appear to be shorter due to a delay in cartilage and bone development. Morphometric studies showed reduction in growth plate and bone formation. These defects did not affect bone mineralization, although the volume of primary bone and levels of osteocalcin and osterix were higher. Other skeletal malformations were observed including fused sternebrae, reduced mineralization in the skull, medial and metacarpal phalanges. Primary cilia from chondrocytes, osteoblasts, and embryonic fibroblasts (MEFs) isolated from knockout mice were shorter and fewer cells had primary cilia in comparison to cells from wild-type mice. In addition, Spag17 knockdown in wild-type MEFs by Spag17 siRNA duplex reproduced the shorter primary cilia phenotype. Our findings disclosed unexpected functions for Spag17 in the regulation of skeletal growth and mineralization, perhaps because of its role in primary cilia of chondrocytes and osteoblasts.

The CODATwins Project: The Cohort Description of Collaborative Project of Development of Anthropometrical Measures in Twins to Study Macro-Environmental Variation in Genetic and Environmental Effects on Anthropometric Traits

For over 100 years, the genetics of human anthropometric traits has attracted scientific interest. In particular, height and body mass index (BMI, calculated as kg/m2) have been under intensive genetic research. However, it is still largely unknown whether and how heritability estimates vary between human populations. Opportunities to address this question have increased recently because of the establishment of many new twin cohorts and the increasing accumulation of data in established twin cohorts. We started a new research project to analyze systematically (1) the variation of heritability estimates of height, BMI and their trajectories over the life course between birth cohorts, ethnicities and countries, and (2) to study the effects of birth-related factors, education and smoking on these anthropometric traits and whether these effects vary between twin cohorts. We identified 67 twin projects, including both monozygotic (MZ) and dizygotic (DZ) twins, using various sources. We asked for individual level data on height and weight including repeated measurements, birth related traits, background variables, education and smoking. By the end of 2014, 48 projects participated. Together, we have 893,458 height and weight measures (52% females) from 434,723 twin individuals, including 201,192 complete twin pairs (40% monozygotic, 40% same-sex dizygotic and 20% opposite-sex dizygotic) representing 22 countries. This project demonstrates that large-scale international twin studies are feasible and can promote the use of existing data for novel research purposes.

Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. ¹H Nuclear Magnetic Resonance (¹H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10⁻³²), PRODH with proline (P-value  = 1.11×10⁻¹⁹), SLC16A9 with carnitine level (P-value  = 4.81×10⁻¹⁴) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10⁻¹⁹) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10⁻⁸), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10⁻⁸) and 2p12 locus with valine (P-value  = 3.49×10⁻⁸). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution ¹H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.

Human metabolic individuality is under strict control of genetic and environmental factors. In our study, we aimed to find the genetic determinants of circulating molecules in sera of large set of individuals representing the general population. First, we performed a hypothesis-free genome wide screen in this population to identify genetic regions of interest. Our study confirmed four known gene metabolite connections, but also pointed to four novel ones. Genome-wide screens enriched for common intergenic variants may miss causal genetic variations directly changing the protein sequence. To investigate this further, we zoomed into regions of interest and tested whether the association signals obtained in the first stage were direct, or whether they represent causal variations, which were not captured in the initial panel. These subsequent tests showed that protein coding and regulatory variations are involved in metabolite levels. For two genomic regions we also found that genes harbour more than one causal variant influencing metabolite levels independent of each other. We also observed strong connection between markers of cardio-metabolic health and metabolites. Taken together, our novel loci are of interest for further research to investigate the causal relation to for instance type 2 diabetes and cardiovascular disease.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

A genome-wide association study of limb bone length using a Large White × Minzhu intercross population

Background

In pig, limb bone length influences ham yield and body height to a great extent and has important economic implications for pig industry. In this study, an intercross population was constructed between the indigenous Chinese Minzhu pig breed and the western commercial Large White pig breed to examine the genetic basis for variation in limb bone length. The aim of this study was to detect potential genetic variants associated with porcine limb bone length.

Methods

A total of 571 F2 individuals from a Large White and Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip, and phenotyped for femur length (FL), humerus length (HL), hipbone length (HIPL), scapula length (SL), tibia length (TL), and ulna length (UL). A genome-wide association study was performed by applying the previously reported approach of genome-wide rapid association using mixed model and regression. Statistical significance of the associations was based on Bonferroni-corrected P-values.

Results

A total of 39 significant SNPs were mapped to a 11.93 Mb long region on pig chromosome 7 (SSC7). Linkage analysis of these significant SNPs revealed three haplotype blocks of 495 kb, 376 kb and 492 kb, respectively, in the 11.93 Mb region. Annotation based on the pig reference genome identified 15 genes that were located near or contained the significant SNPs in these linkage disequilibrium intervals. Conditioned analysis revealed that four SNPs, one on SSC2 and three on SSC4, showed significant associations with SL and HL, respectively.

Conclusions

Analysis of the 15 annotated genes that were identified in these three haplotype blocks indicated that HMGA1 and PPARD, which are expressed in limbs and influence chondrocyte cell growth and differentiation, could be considered as relevant biological candidates for limb bone length in pig, with potential applications in breeding programs. Our results may also be useful for the study of the mechanisms that underlie human limb length and body height.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0056-6) contains supplementary material, which is available to authorized users.

Spatial localization of recent ancestors for admixed individuals

Ancestry analysis from genetic data plays a critical role in studies of human disease and evolution. Recent work has introduced explicit models for the geographic distribution of genetic variation and has shown that such explicit models yield superior accuracy in ancestry inference over nonmodel-based methods. Here we extend such work to introduce a method that models admixture between ancestors from multiple sources across a geographic continuum. We devise efficient algorithms based on hidden Markov models to localize on a map the recent ancestors (e.g., grandparents) of admixed individuals, joint with assigning ancestry at each locus in the genome. We validate our methods by using empirical data from individuals with mixed European ancestry from the Population Reference Sample study and show that our approach is able to localize their recent ancestors within an average of 470 km of the reported locations of their grandparents. Furthermore, simulations from real Population Reference Sample genotype data show that our method attains high accuracy in localizing recent ancestors of admixed individuals in Europe (an average of 550 km from their true location for localization of two ancestries in Europe, four generations ago). We explore the limits of ancestry localization under our approach and find that performance decreases as the number of distinct ancestries and generations since admixture increases. Finally, we build a map of expected localization accuracy across admixed individuals according to the location of origin within Europe of their ancestors.

Adaptive, convergent origins of the pygmy phenotype in African rainforest hunter-gatherers

The evolutionary history of the human pygmy phenotype (small body size), a characteristic of African and Southeast Asian rainforest hunter-gatherers, is largely unknown. Here we use a genome-wide admixture mapping analysis to identify 16 genomic regions that are significantly associated with the pygmy phenotype in the Batwa, a rainforest hunter-gatherer population from Uganda (east central Africa). The identified genomic regions have multiple attributes that provide supporting evidence of genuine association with the pygmy phenotype, including enrichments for SNPs previously associated with stature variation in Europeans and for genes with growth hormone receptor and regulation functions. To test adaptive evolutionary hypotheses, we computed the haplotype-based integrated haplotype score (iHS) statistic and the level of population differentiation (FST) between the Batwa and their agricultural neighbors, the Bakiga, for each genomic SNP. Both |iHS| and FST values were significantly higher for SNPs within the Batwa pygmy phenotype-associated regions than the remainder of the genome, a signature of polygenic adaptation. In contrast, when we expanded our analysis to include Baka rainforest hunter-gatherers from Cameroon and Gabon (west central Africa) and Nzebi and Nzime neighboring agriculturalists, we did not observe elevated |iHS| or FST values in these genomic regions. Together, these results suggest adaptive and at least partially convergent origins of the pygmy phenotype even within Africa, supporting the hypothesis that small body size confers a selective advantage for tropical rainforest hunter-gatherers but raising questions about the antiquity of this behavior.

A population genetic signal of polygenic adaptation

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results.

The process of adaptation is of fundamental importance in evolutionary biology. Within the last few decades, genotyping technologies and new statistical methods have given evolutionary biologists the ability to identify individual regions of the genome that are likely to have been important in this process. When adaptation occurs in traits that are underwritten by many genes, however, the genetic signals left behind are more diffuse, and no individual region of the genome is likely to show strong signatures of selection. Identifying this signature therefore requires a detailed annotation of sites associated with a particular phenotype. Here we develop and implement a suite of statistical methods to integrate this sort of annotation from genome wide association studies with allele frequency data from many populations, providing a powerful way to identify the signal of adaptation in polygenic traits. We apply our methods to test for the impact of selection on human height, skin pigmentation, body mass index, type 2 diabetes risk, and inflammatory bowel disease risk. We find relatively strong signals for height and skin pigmentation, moderate signals for inflammatory bowel disease, and comparatively little evidence for body mass index and type 2 diabetes risk.

Whole-exome imputation of sequence variants identified two novel alleles associated with adult body height in African Americans

Adult body height is a quantitative trait for which genome-wide association studies (GWAS) have identified numerous loci, primarily in European populations. These loci, comprising common variants, explain <10% of the phenotypic variance in height. We searched for novel associations between height and common (minor allele frequency, MAF ≥5%) or infrequent (0.5% < MAF < 5%) variants across the exome in African Americans. Using a reference panel of 1692 African Americans and 471 Europeans from the National Heart, Lung, and Blood Institute's (NHLBI) Exome Sequencing Project (ESP), we imputed whole-exome sequence data into 13 719 African Americans with existing array-based GWAS data (discovery). Variants achieving a height-association threshold of P < 5E-06 in the imputed dataset were followed up in an independent sample of 1989 African Americans with whole-exome sequence data (replication). We used P < 2.5E-07 (=0.05/196 779 variants) to define statistically significant associations in meta-analyses combining the discovery and replication sets (N = 15 708). We discovered and replicated three independent loci for association: 5p13.3/C5orf22/rs17410035 (MAF = 0.10, β = 0.64 cm, P = 8.3E-08), 13q14.2/SPRYD7/rs114089985 (MAF = 0.03, β = 1.46 cm, P = 4.8E-10) and 17q23.3/GH2/rs2006123 (MAF = 0.30; β = 0.47 cm; P = 4.7E-09). Conditional analyses suggested 5p13.3 (C5orf22/rs17410035) and 13q14.2 (SPRYD7/rs114089985) may harbor novel height alleles independent of previous GWAS-identified variants (r(2) with GWAS loci <0.01); whereas 17q23.3/GH2/rs2006123 was correlated with GWAS-identified variants in European and African populations. Notably, 13q14.2/rs114089985 is infrequent in African Americans (MAF = 3%), extremely rare in European Americans (MAF = 0.03%), and monomorphic in Asian populations, suggesting it may be an African-American-specific height allele. Our findings demonstrate that whole-exome imputation of sequence variants can identify low-frequency variants and discover novel variants in non-European populations.