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.Electronic supplementary materialThe online version of this article (doi:10.1007/s00439-015-1559-0) contains supplementary material, which is available to authorized users.

No abstract

Next-generation sequencing (NGS) technologies offer immense possibilities given the large genomic data they simultaneously deliver. The human Y-chromosome serves as good example how NGS benefits various applications in evolution, anthropology, genealogy, and forensics. Prior to NGS, the Y-chromosome phylogenetic tree consisted of a few hundred branches, based on NGS data, it now contains many thousands. The complexity of both, Y tree and NGS data provide challenges for haplogroup assignment. For effective analysis and interpretation of Y-chromosome NGS data, we present Yleaf, a publically available, automated, user-friendly software for high-resolution Y-chromosome haplogroup inference independently of library and sequencing methods.

SNPs from the non-recombining part of the human Y chromosome (Y-SNPs) are informative to classify paternal lineages in forensic, genealogical, anthropological, and evolutionary studies. Although thousands of Y-SNPs were identified thus far, previous Y-SNP multiplex tools target only dozens of markers simultaneously, thereby restricting the provided Y-haplogroup resolution and limiting their applications. Here, we overcome this shortcoming by introducing a high-resolution multiplex tool for parallel genotyping-by-sequencing of 530 Y-SNPs using the Ion Torrent PGM platform, which allows classification of 432 worldwide Y haplogroups. Contrary to previous Y-SNP multiplex tools, our approach covers branches of the entire Y tree, thereby maximizing the paternal lineage classification obtainable. We used a default DNA input amount of 10 ng per reaction but preliminary sensitivity testing revealed positive results from as little as 100 pg input DNA. Furthermore, we demonstrate that sample pooling using barcodes is feasible, allowing increased throughput for lower per-sample costs. In addition to the wetlab protocol, we provide a software tool for automated data quality control and haplogroup classification. The unique combination of ultra-high marker density and high sensitivity achievable from low amounts of potentially degraded DNA makes this new multiplex tool suitable for a wide range of Y-chromosome applications.

BackgroundCompound Heterozygosity (CH) in classical genetics is the presence of two different recessive mutations at a particular gene locus. A relaxed form of CH alleles may account for an essential proportion of the missing heritability, i.e. heritability of phenotypes so far not accounted for by single genetic variants. Methods to detect CH-like effects in genome-wide association studies (GWAS) may facilitate explaining the missing heritability, but to our knowledge no viable software tools for this purpose are currently available.ResultsIn this work we present the Generalized Compound Double Heterozygosity (GCDH) test and its implementation in the R package CollapsABEL. Time-consuming procedures are optimized for computational efficiency using Java or C++. Intermediate results are stored either in an SQL database or in a so-called big.matrix file to achieve reasonable memory footprint. Our large scale simulation studies show that GCDH is capable of discovering genetic associations due to CH-like interactions with much higher power than a conventional single-SNP approach under various settings, whether the causal genetic variations are available or not. CollapsABEL provides a user-friendly pipeline for genotype collapsing, statistical testing, power estimation, type I error control and graphics generation in the R language.ConclusionsCollapsABEL provides a computationally efficient solution for screening general forms of CH alleles in densely imputed microarray or whole genome sequencing datasets. The GCDH test provides an improved power over single-SNP based methods in detecting the prevalence of CH in human complex phenotypes, offering an opportunity for tackling the missing heritability problem.Binary and source packages of CollapsABEL are available on CRAN (https://cran.r-project.org/web/packages/CollapsABEL) and the website of the GenABEL project (http://www.genabel.org/packages).Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1006-9) contains supplementary material, which is available to authorized users.

Adult height is the most widely genetically studied common trait in humans; however, the trait variance explainable by currently known height-associated single nucleotide polymorphisms (SNPs) identified from the previous genome-wide association studies (GWAS) is yet far from complete given the high heritability of this complex trait. To exam if compound heterozygotes (CH) may explain extra height variance, we conducted a genome-wide analysis to screen for CH in association with adult height in 10,631 Dutch Europeans enriched with extremely tall people, using our recently developed method implemented in the software package CollapsABEL. The analysis identified six regions (3q23, 5q35.1, 6p21.31, 6p21.33, 7q21.2, and 9p24.3), where multiple pairs of SNPs as CH showed genome-wide significant association with height (P < 1.67 × 10−10). Of those, 9p24.3 represents a novel region influencing adult height, whereas the others have been highlighted in the previous GWAS on height based on analysis of individual SNPs. A replication analysis in 4080 Australians of European ancestry confirmed the significant CH-like association at 9p24.3 (P < 0.05). Together, the collapsed genotypes at these six loci explained 2.51% of the height variance (after adjusting for sex and age), compared with 3.23% explained by the 14 top-associated SNPs at 14 loci identified by traditional GWAS in the same data set (P < 5 × 10−8). Overall, our study empirically demonstrates that CH plays an important role in adult height and may explain a proportion of its “missing heritability”. Moreover, our findings raise promising expectations for other highly polygenic complex traits to explain missing heritability identifiable through CH-like associations.Electronic supplementary materialThe online version of this article (doi:10.1007/s00439-017-1842-3) contains supplementary material, which is available to authorized users.

Actinic keratosis (AK) is a skin disease frequently found in European elderly, and it represents the precursor of cutaneous squamous cell carcinoma. Our recent genome-wide association study highlighted DNA variants in two pigmentation genes, IRF4 and MC1R, that confer AK risk in Europeans. Here, we performed a genome-wide search for relaxed forms of compound heterozygosity in association with AK using our recently developed software CollapsABEL. In a discovery dataset of 3,193 Dutch Europeans, a total of 15 genetic loci showed genome-wide significant association with AK (P < 1.25 × 10). Of those, three loci (6p21.2, 6p12.2, and 6q13) were confirmed in a replication dataset that included 624 additional Dutch Europeans (P < 0.05). These replicated loci harbored six genes (KCNK5/KCNK17, PAQR8/GSTA2, and KCNQ5/KHDC1), none of them known to be involved in pigmentation. A candidate compound heterozygosity analysis for 12 pigmentation loci highlighted SLC24A4 at 14q32.12 as showing significant association with AK (P = 8.83 × 10). The four significantly AK-associated compound heterozygosity single-nucleotide polymorphism pairs together explained 4.37% of the total AK variation, which was 2.62 times greater than the two top-associated individual single nucleotide polymorphisms together (1.67%) identified in the previous conventional genome-wide association study. In conclusion, CollapsABEL showed compound heterozygosity in non-pigmentation- and pigmentation-related loci conferring genetic risk of AK.

Predicting adult height from DNA has important implications in forensic DNA phenotyping. In 2014, we introduced a prediction model consisting of 180 height-associated SNPs based on data from 10,361 Northwestern Europeans enriched with tall individuals (770 > 1.88 standard deviation), which yielded a mid-ranged accuracy (AUC = 0.75 for binary prediction of tall stature and R 2 = 0.12 for quantitative prediction of adult height). Here, we provide an update on DNA-based height predictability considering an enlarged list of subsequentlypublished height-associated SNPs using data from the same set of 10,361 Europeans. A prediction model based on the full set of 689 SNPs showed an improved accuracy relative to previous models for both tall stature (AUC = 0.79) and quantitative height (R 2 = 0.21). A feature selection analysis revealed a subset of 412 most informative SNPs while the corresponding prediction model retained most of the accuracy (AUC = 0.76 and R 2 = 0.19) achieved with the full model. Over all, our study empirically exemplifies that the accuracy for predicting human appearance phenotypes with very complex underlying genetic architectures, such as adult height, can be improved by increasing the number of phenotype-associated DNA variants. Our work also demonstrates that a careful sub-selection allows for a considerable reduction of the number of DNA predictors that achieve similar prediction accuracy as provided by the full set. This is forensically relevant due to restrictions in the number of SNPs simultaneously analyzable with forensically suitable DNA technologies in the current days of targeted massively parallel sequencing in forensic genetics.