A genome-wide scan for genes under balancing selection in Drosophila melanogaster.

BACKGROUND: In the history of population genetics balancing selection has been considered as an important evolutionary force, yet until today little is known about its abundance and its effect on patterns of genetic diversity. Several well-known examples of balancing selection have been reported from humans, mice, plants, and parasites. However, only very few systematic studies have been carried out to detect genes under balancing selection. We performed a genome scan in Drosophila melanogaster to find signatures of balancing selection in a derived (European) and an ancestral (African) population. We screened a total of 34 genomes searching for regions of high genetic diversity and an excess of SNPs with intermediate frequency. RESULTS: In total, we found 183 candidate genes: 141 in the European population and 45 in the African one, with only three genes shared between both populations. Most differences between both populations were observed on the X chromosome, though this might be partly due to false positives. Functionally, we find an overrepresentation of genes involved in neuronal development and circadian rhythm. Furthermore, some of the top genes we identified are involved in innate immunity. CONCLUSION: Our results revealed evidence of genes under balancing selection in European and African populations. More candidate genes have been found in the European population. They are involved in several different functions.

Global skin colour prediction from DNA.

Human skin colour is highly heritable and externally visible with relevance in medical, forensic, and anthropological genetics. Although eye and hair colour can already be predicted with high accuracies from small sets of carefully selected DNA markers, knowledge about the genetic predictability of skin colour is limited. Here, we investigate the skin colour predictive value of 77 single-nucleotide polymorphisms (SNPs) from 37 genetic loci previously associated with human pigmentation using 2025 individuals from 31 global populations. We identified a minimal set of 36 highly informative skin colour predictive SNPs and developed a statistical prediction model capable of skin colour prediction on a global scale. Average cross-validated prediction accuracies expressed as area under the receiver-operating characteristic curve (AUC) ± standard deviation were 0.97 ± 0.02 for Light, 0.83 ± 0.11 for Dark, and 0.96 ± 0.03 for Dark-Black. When using a 5-category, this resulted in 0.74 ± 0.05 for Very Pale, 0.72 ± 0.03 for Pale, 0.73 ± 0.03 for Intermediate, 0.87±0.1 for Dark, and 0.97 ± 0.03 for Dark-Black. A comparative analysis in 194 independent samples from 17 populations demonstrated that our model outperformed a previously proposed 10-SNP-classifier approach with AUCs rising from 0.79 to 0.82 for White, comparable at the intermediate level of 0.63 and 0.62, respectively, and a large increase from 0.64 to 0.92 for Black. Overall, this study demonstrates that the chosen DNA markers and prediction model, particularly the 5-category level; allow skin colour predictions within and between continental regions for the first time, which will serve as a valuable resource for future applications in forensic and anthropologic genetics.

Population genetic evidence for cold adaptation in European Drosophila melanogaster populations.

We studied Drosophila melanogaster populations from Europe (the Netherlands and France) and Africa (Rwanda and Zambia) to uncover genetic evidence of adaptation to cold. We present here four lines of evidence for genes involved in cold adaptation from four perspectives: (i) the frequency of SNPs at genes previously known to be associated with chill-coma recovery time (CCRT), startle reflex (SR) and resistance to starvation stress (RSS) vary along environmental gradients and therefore among populations; (ii) SNPs of genes that correlate significantly with latitude and altitude in African and European populations overlap with SNPs that correlate with a latitudinal cline from North America; (iii) at the genomewide level, the top candidate genes are enriched in gene ontology (GO) terms that are related to cold tolerance; (iv) GO enriched terms from North American clinal genes overlap significantly with those from Africa and Europe. Each SNP was tested in 10 independent runs of Bayenv2, using the median Bayes factors to ascertain candidate genes. None of the candidate genes were found close to the breakpoints of cosmopolitan inversions, and only four candidate genes were linked to QTLs related to CCRT. To overcome the limitation that we used only four populations to test correlations with environmental gradients, we performed simulations to estimate the power of our approach for detecting selection. Based on our results, we propose a novel network of genes that is involved in cold adaptation.

A comprehensive molecular study on Coffin-Siris and Nicolaides-Baraitser syndromes identifies a broad molecular and clinical spectrum converging on altered chromatin remodeling.

Chromatin remodeling complexes are known to modify chemical marks on histones or to induce conformational changes in the chromatin in order to regulate transcription. De novo dominant mutations in different members of the SWI/SNF chromatin remodeling complex have recently been described in individuals with Coffin-Siris (CSS) and Nicolaides-Baraitser (NCBRS) syndromes. Using a combination of whole-exome sequencing, NGS-based sequencing of 23 SWI/SNF complex genes, and molecular karyotyping in 46 previously undescribed individuals with CSS and NCBRS, we identified a de novo 1-bp deletion (c.677delG, p.Gly226Glufs*53) and a de novo missense mutation (c.914G>T, p.Cys305Phe) in PHF6 in two individuals diagnosed with CSS. PHF6 interacts with the nucleosome remodeling and deacetylation (NuRD) complex implicating dysfunction of a second chromatin remodeling complex in the pathogenesis of CSS-like phenotypes. Altogether, we identified mutations in 60% of the studied individuals (28/46), located in the genes ARID1A, ARID1B, SMARCB1, SMARCE1, SMARCA2, and PHF6. We show that mutations in ARID1B are the main cause of CSS, accounting for 76% of identified mutations. ARID1B and SMARCB1 mutations were also found in individuals with the initial diagnosis of NCBRS. These individuals apparently belong to a small subset who display an intermediate CSS/NCBRS phenotype. Our proposed genotype-phenotype correlations are important for molecular screening strategies.

Genetics of skin color variation in Europeans: genome-wide association studies with functional follow-up.

In the International Visible Trait Genetics (VisiGen) Consortium, we investigated the genetics of human skin color by combining a series of genome-wide association studies (GWAS) in a total of 17,262 Europeans with functional follow-up of discovered loci. Our GWAS provide the first genome-wide significant evidence for chromosome 20q11.22 harboring the ASIP gene being explicitly associated with skin color in Europeans. In addition, genomic loci at 5p13.2 (SLC45A2), 6p25.3 (IRF4), 15q13.1 (HERC2/OCA2), and 16q24.3 (MC1R) were confirmed to be involved in skin coloration in Europeans. In follow-up gene expression and regulation studies of 22 genes in 20q11.22, we highlighted two novel genes EIF2S2 and GSS, serving as competing functional candidates in this region and providing future research lines. A genetically inferred skin color score obtained from the 9 top-associated SNPs from 9 genes in 940 worldwide samples (HGDP-CEPH) showed a clear gradual pattern in Western Eurasians similar to the distribution of physical skin color, suggesting the used 9 SNPs as suitable markers for DNA prediction of skin color in Europeans and neighboring populations, relevant in future forensic and anthropological investigations.

GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans.

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.

A genome-wide association study identifies five loci influencing facial morphology in Europeans.

Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes--PRDM16, PAX3, TP63, C5orf50, and COL17A1--in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

Denisova admixture and the first modern human dispersals into Southeast Asia and Oceania.

It has recently been shown that ancestors of New Guineans and Bougainville Islanders have inherited a proportion of their ancestry from Denisovans, an archaic hominin group from Siberia. However, only a sparse sampling of populations from Southeast Asia and Oceania were analyzed. Here, we quantify Denisova admixture in 33 additional populations from Asia and Oceania. Aboriginal Australians, Near Oceanians, Polynesians, Fijians, east Indonesians, and Mamanwa (a "Negrito" group from the Philippines) have all inherited genetic material from Denisovans, but mainland East Asians, western Indonesians, Jehai (a Negrito group from Malaysia), and Onge (a Negrito group from the Andaman Islands) have not. These results indicate that Denisova gene flow occurred into the common ancestors of New Guineans, Australians, and Mamanwa but not into the ancestors of the Jehai and Onge and suggest that relatives of present-day East Asians were not in Southeast Asia when the Denisova gene flow occurred. Our finding that descendants of the earliest inhabitants of Southeast Asia do not all harbor Denisova admixture is inconsistent with a history in which the Denisova interbreeding occurred in mainland Asia and then spread over Southeast Asia, leading to all its earliest modern human inhabitants. Instead, the data can be most parsimoniously explained if the Denisova gene flow occurred in Southeast Asia itself. Thus, archaic Denisovans must have lived over an extraordinarily broad geographic and ecological range, from Siberia to tropical Asia.

Comprehensive candidate gene study highlights UGT1A and BNC2 as new genes determining continuous skin color variation in Europeans.

Natural variation in human skin pigmentation is primarily due to genetic causes rooted in recent evolutionary history. Genetic variants associated with human skin pigmentation confer risk of skin cancer and may provide useful information in forensic investigations. Almost all previous gene-mapping studies of human skin pigmentation were based on categorical skin color information known to oversimplify the continuous nature of human skin coloration. We digitally quantified skin color into hue and saturation dimensions for 5,860 Dutch Europeans based on high-resolution skin photographs. We then tested an extensive list of 14,185 single nucleotide polymorphisms in 281 candidate genes potentially involved in human skin pigmentation for association with quantitative skin color phenotypes. Confirmatory association was revealed for several known skin color genes including HERC2, MC1R, IRF4, TYR, OCA2, and ASIP. We identified two new skin color genes: genetic variants in UGT1A were significantly associated with hue and variants in BNC2 were significantly associated with saturation. Overall, digital quantification of human skin color allowed detecting new skin color genes. The variants identified in this study may also contribute to the risk of skin cancer. Our findings are also important for predicting skin color in forensic investigations.

Mutability of Y-chromosomal microsatellites: rates, characteristics, molecular bases, and forensic implications.

Nonrecombining Y-chromosomal microsatellites (Y-STRs) are widely used to infer population histories, discover genealogical relationships, and identify males for criminal justice purposes. Although a key requirement for their application is reliable mutability knowledge, empirical data are only available for a small number of Y-STRs thus far. To rectify this, we analyzed a large number of 186 Y-STR markers in nearly 2000 DNA-confirmed father-son pairs, covering an overall number of 352,999 meiotic transfers. Following confirmation by DNA sequence analysis, the retrieved mutation data were modeled via a Bayesian approach, resulting in mutation rates from 3.78 × 10(-4) (95% credible interval [CI], 1.38 × 10(-5) - 2.02 × 10(-3)) to 7.44 × 10(-2) (95% CI, 6.51 × 10(-2) - 9.09 × 10(-2)) per marker per generation. With the 924 mutations at 120 Y-STR markers, a nonsignificant excess of repeat losses versus gains (1.16:1), as well as a strong and significant excess of single-repeat versus multirepeat changes (25.23:1), was observed. Although the total repeat number influenced Y-STR locus mutability most strongly, repeat complexity, the length in base pairs of the repeated motif, and the father's age also contributed to Y-STR mutability. To exemplify how to practically utilize this knowledge, we analyzed the 13 most mutable Y-STRs in an independent sample set and empirically proved their suitability for distinguishing close and distantly related males. This finding is expected to revolutionize Y-chromosomal applications in forensic biology, from previous male lineage differentiation toward future male individual identification.

Digital quantification of human eye color highlights genetic association of three new loci.

Previous studies have successfully identified genetic variants in several genes associated with human iris (eye) color; however, they all used simplified categorical trait information. Here, we quantified continuous eye color variation into hue and saturation values using high-resolution digital full-eye photographs and conducted a genome-wide association study on 5,951 Dutch Europeans from the Rotterdam Study. Three new regions, 1q42.3, 17q25.3, and 21q22.13, were highlighted meeting the criterion for genome-wide statistically significant association. The latter two loci were replicated in 2,261 individuals from the UK and in 1,282 from Australia. The LYST gene at 1q42.3 and the DSCR9 gene at 21q22.13 serve as promising functional candidates. A model for predicting quantitative eye colors explained over 50% of trait variance in the Rotterdam Study. Over all our data exemplify that fine phenotyping is a useful strategy for finding genes involved in human complex traits.

Comprehensive mutation analysis of 17 Y-chromosomal short tandem repeat polymorphisms included in the AmpFlSTR Yfiler PCR amplification kit.

The Y-chromosomal short tandem repeat (Y-STR) polymorphisms included in the AmpFlSTR Yfiler polymerase chain reaction amplification kit have become widely used for forensic and evolutionary applications where a reliable knowledge on mutation properties is necessary for correct data interpretation. Therefore, we investigated the 17 Yfiler Y-STRs in 1,730-1,764 DNA-confirmed father-son pairs per locus and found 84 sequence-confirmed mutations among the 29,792 meiotic transfers covered. Of the 84 mutations, 83 (98.8%) were single-repeat changes and one (1.2%) was a double-repeat change (ratio, 1:0.01), as well as 43 (51.2%) were repeat gains and 41 (48.8%) repeat losses (ratio, 1:0.95). Medians from Bayesian estimation of locus-specific mutation rates ranged from 0.0003 for DYS448 to 0.0074 for DYS458, with a median rate across all 17 Y-STRs of 0.0025. The mean age (at the time of son's birth) of fathers with mutations was with 34.40 (+/-11.63) years higher than that of fathers without ones at 30.32 (+/-10.22) years, a difference that is highly statistically significant (p < 0.001). A Poisson-based modeling revealed that the Y-STR mutation rate increased with increasing father's age on a statistically significant level (alpha = 0.0294, 2.5% quantile = 0.0001). From combining our data with those previously published, considering all together 135,212 meiotic events and 331 mutations, we conclude for the Yfiler Y-STRs that (1) none had a mutation rate of >1%, 12 had mutation rates of >0.1% and four of <0.1%, (2) single-repeat changes were strongly favored over multiple-repeat ones for all loci but 1 and (3) considerable variation existed among loci in the ratio of repeat gains versus losses. Our finding of three Y-STR mutations in one father-son pair (and two pairs with two mutations each) has consequences for determining the threshold of allelic differences to conclude exclusion constellations in future applications of Y-STRs in paternity testing and pedigree analyses.

Efficacy assessment of SNP sets for genome-wide disease association studies.

The power of a genome-wide disease association study depends critically upon the properties of the marker set used, particularly the number and physical spacing of markers, and the level of inter-marker association due to linkage disequilibrium. Extending our previously devised theoretical framework for the entropy-based selection of genetic markers, we have developed a local measure of the efficacy of a marker set, relative to including a maximally polymorphic single nucleotide polymorphism (SNP) at the map position of interest. Using this quantitative criterion, we evaluated five currently available SNP sets, namely Affymetrix 100K and 500K, and Illumina 100K, 300K and 550K in the CEU, YRI and JPT + CHB HapMap populations. At 50% relative efficacy, the commercial marker sets cover between 19 and 68% of the human genome, depending upon the population under study. An optimal technology-independent 500K marker set constructed from HapMap for Caucasians, in contrast, would achieve 73% coverage at the same relative efficacy.

Novel quantitative pigmentation phenotyping enhances genetic association, epistasis, and prediction of human eye colour.

Success of genetic association and the prediction of phenotypic traits from DNA are known to depend on the accuracy of phenotype characterization, amongst other parameters. To overcome limitations in the characterization of human iris pigmentation, we introduce a fully automated approach that specifies the areal proportions proposed to represent differing pigmentation types, such as pheomelanin, eumelanin, and non-pigmented areas within the iris. We demonstrate the utility of this approach using high-resolution digital eye imagery and genotype data from 12 selected SNPs from over 3000 European samples of seven populations that are part of the EUREYE study. In comparison to previous quantification approaches, (1) we achieved an overall improvement in eye colour phenotyping, which provides a better separation of manually defined eye colour categories. (2) Single nucleotide polymorphisms (SNPs) known to be involved in human eye colour variation showed stronger associations with our approach. (3) We found new and confirmed previously noted SNP-SNP interactions. (4) We increased SNP-based prediction accuracy of quantitative eye colour. Our findings exemplify that precise quantification using the perceived biological basis of pigmentation leads to enhanced genetic association and prediction of eye colour. We expect our approach to deliver new pigmentation genes when applied to genome-wide association testing.

GENOMIZER: an integrated analysis system for genome-wide association data.

Genome-wide association analysis appears to be a promising way to identify heritable susceptibility factors for complex human disorders. However, the feasibility of large-scale genotyping experiments is currently limited by an incomplete marker coverage of the genome, a restricted understanding of the functional role of given genomic regions, and the small sample sizes used. Thus, genome-wide association analysis will be a screening tool to facilitate subsequent gene discovery rather than a means to completely resolve individual genetic risk profiles. The validation of association findings will continue to rely upon the replication of "leads" in independent samples from either the same or different populations. Even under such pragmatic conditions, the timely analysis of the large data sets in question poses serious technical challenges. We have therefore developed public-domain software, GENOMIZER, that implements the workflow of an association experiment, including data management, single-point and haplotype analysis, "lead" definition, and data visualization. GENOMIZER (www.ikmb.uni-kiel.de/genomizer) comes with a complete user manual, and is open-source software licensed under the GNU Lesser General Public License. We suggest that the use of this software will facilitate the handling and interpretation of the currently emerging genome-wide association data.

An Automatic 3D Facial Landmarking Algorithm Using 2D Gabor Wavelets.

In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend an established 2D landmarking method for simultaneous evaluation of these data. The method is validated by performing landmarking experiments on two data sets using 21 landmarks and compared with an active shape model implementation. On average, landmarking error for our method was 1.9 mm, whereas the active shape model resulted in an average landmarking error of 2.3 mm. A second study investigating facial shape heritability in related individuals concludes that automatic landmarking is on par with manual landmarking for some landmarks. Our algorithm can be trained in 30 min to automatically landmark 3D facial data sets of any size, and allows for fast and robust landmarking of 3D faces.

The MC1R Gene and Youthful Looks.

Looking young for one's age has been a desire since time immemorial. This desire is attributable to the belief that appearance reflects health and fecundity. Indeed, perceived age predicts survival [1] and associates with molecular markers of aging such as telomere length [2]. Understanding the underlying molecular biology of perceived age is vital for identifying new aging therapies among other purposes, but studies are lacking thus far. As a first attempt, we performed genome-wide association studies (GWASs) of perceived facial age and wrinkling estimated from digital facial images by analyzing over eight million SNPs in 2,693 elderly Dutch Europeans from the Rotterdam Study. The strongest genetic associations with perceived facial age were found for multiple SNPs in the MC1R gene (p < 1 × 10(-7)). This effect was enhanced for a compound heterozygosity marker constructed from four pre-selected functional MC1R SNPs (p = 2.69 × 10(-12)), which was replicated in 599 Dutch Europeans from the Leiden Longevity Study (p = 0.042) and in 1,173 Europeans of the TwinsUK Study (p = 3 × 10(-3)). Individuals carrying the homozygote MC1R risk haplotype looked on average up to 2 years older than non-carriers. This association was independent of age, sex, skin color, and sun damage (wrinkling, pigmented spots) and persisted through different sun-exposure levels. Hence, a role for MC1R in youthful looks independent of its known melanin synthesis function is suggested. Our study uncovers the first genetic evidence explaining why some people look older for their age and provides new leads for further investigating the biological basis of how old or young people look.

Detecting individual ancestry in the human genome.

Detecting and quantifying the population substructure present in a sample of individuals are of main interest in the fields of genetic epidemiology, population genetics, and forensics among others. To date, several algorithms have been proposed for estimating the amount of genetic ancestry within an individual. In the present review, we introduce the most widely used methods in population genetics for detecting individual genetic ancestry. We further show, by means of simulations, the performance of popular algorithms for detecting individual ancestry in various controlled demographic scenarios. Finally, we provide some hints on how to interpret the results from these algorithms.

Inferring positive selection in humans from genomic data.

Adaptation can be described as an evolutionary process that leads to an adjustment of the phenotypes of a population to their environment. In the classical view, new mutations can introduce novel phenotypic features into a population that leave footprints in the genome after fixation, such as selective sweeps. Alternatively, existing genetic variants may become beneficial after an environmental change and increase in frequency. Although they may not reach fixation, they may cause a shift of the optimum of a phenotypic trait controlled by multiple loci. With the availability of polymorphism data from various organisms, including humans and chimpanzees, it has become possible to detect molecular evidence of adaptation and to estimate the strength and target of positive selection. In this review, we discuss the two competing models of adaptation and suitable approaches for detecting the footprints of positive selection on the molecular level.