A genome-wide association study identifies novel alleles associated with hair color and skin pigmentation

We conducted a multi-stage genome-wide association study of natural hair color in more than 10,000 men and women of European ancestry from the United States and Australia. An initial analysis of 528,173 single nucleotide polymorphisms (SNPs) genotyped on 2,287 women identified IRF4 and SLC24A4 as loci highly associated with hair color, along with three other regions encompassing known pigmentation genes. We confirmed these associations in 7,028 individuals from three additional studies. Across these four studies, SLC24A4 rs12896399 and IRF4 rs12203592 showed strong associations with hair color, with p=6.0×10⁻⁶² and p=7.46×10⁻¹²⁷, respectively. The IRF4 SNP was also associated with skin color (p=6.2×10⁻¹⁴), eye color (p=6.1×10⁻¹³), and skin tanning response to sunlight (p=3.9×10⁻⁸⁹). A multivariable analysis pooling data from the initial GWAS and an additional 1,440 individuals suggested that the association between rs12203592 and hair color was independent of rs1540771, a SNP between the IRF4 and EXOC2 genes previously found to be associated with hair color. After adjustment for rs12203592, the association between rs1540771 and hair color was not significant (p=0.52). One variant in the MATP gene was associated with hair color. A variant in the HERC2 gene upstream of the OCA2 gene showed the strongest and independent association with hair color compared with other SNPs in this region, including three previously reported SNPs. The signals detected in a region around the MC1R gene were explained by MC1R red hair color alleles. Our results suggest that the IRF4 and SLC24A4 loci are associated with human hair color and skin pigmentation.     

Linkage disequilibrium and population-structure analysis among Capsicum annuum L. cultivars for use in association mapping

Knowledge of population structure and linkage disequilibrium among the worldwide collections of peppers currently classified as hot, mild, sweet and ornamental types is indispensable for applying association mapping and genomic selection to improve pepper. The current study aimed to resolve the genetic diversity and relatedness of Capsicum annuum germplasm by use of simple sequence repeat (SSR) loci across all chromosomes in samples collected in 2011 and 2012. The physical distance covered by the entire set of SSRs used was 2,265.9 Mb from the 3.48-Gb hot-pepper genome size. The model-based program STRUCTURE was used to infer five clusters, which was further confirmed by classical molecular-genetic diversity analysis. Mean heterozygosity of various loci was estimated to be 0.15. Linkage disequilibrium (LD) was used to identify 17 LD blocks across various chromosomes with sizes from 0.154 Kb to 126.28 Mb. CAMS-142 of chromosome 1 was significantly associated with both capsaicin (CA) and dihydrocapsaicin (DCA) levels. Further, CAMS-142 was located in an LD block of 98.18 Mb. CAMS-142 amplified bands of 244, 268, 283 and 326 bp. Alleles 268 and 283 bp had positive effects on both CA and DCA levels, with an average R ² of 12.15 % (CA) and 12.3 % (DCA). Eight markers from seven different chromosomes were significantly associated with fruit weight, contributing an average effect of 15 %. CAMS-199, HpmsE082 and CAMS-190 are the three major quantitative trait loci located on chromosomes 8, 9, and 10, respectively, and were associated with fruit weight in samples from both years of the study. This research demonstrates the effectiveness of using genome-wide SSR-based markers to assess features of LD and genetic diversity within C. annuum.     

Identification of QTL for UV-protective eye area pigmentation in cattle by progeny phenotyping and genome-wide association analysis

Pigmentation patterns allow for the differentiation of cattle breeds. A dominantly inherited white head is characteristic for animals of the Fleckvieh (FV) breed. However, a minority of the FV animals exhibits peculiar pigmentation surrounding the eyes (ambilateral circumocular pigmentation, ACOP). In areas where animals are exposed to increased solar ultraviolet radiation, ACOP is associated with a reduced susceptibility to bovine ocular squamous cell carcinoma (BOSCC, eye cancer). Eye cancer is the most prevalent malignant tumour affecting cattle. Selection for animals with ACOP rapidly reduces the incidence of BOSCC. To identify quantitative trait loci (QTL) underlying ACOP, we performed a genome-wide association study using 658,385 single nucleotide polymorphisms (SNPs). The study population consisted of 3579 bulls of the FV breed with a total of 320,186 progeny with phenotypes for ACOP. The proportion of progeny with ACOP was used as a quantitative trait with high heritability (h(2)?=?0.79). A variance component based approach to account for population stratification uncovered twelve QTL regions on seven chromosomes. The identified QTL point to MCM6, PAX3, ERBB3, KITLG, LEF1, DKK2, KIT, CRIM1, ATRN, GSDMC, MITF and NBEAL2 as underlying genes for eye area pigmentation in cattle. The twelve QTL regions explain 44.96% of the phenotypic variance of the proportion of daughters with ACOP. The chromosomes harbouring significantly associated SNPs account for 54.13% of the phenotypic variance, while another 19.51% of the phenotypic variance is attributable to chromosomes without identified QTL. Thus, the missing heritability amounts to 7% only. Our results support a polygenic inheritance pattern of ACOP in cattle and provide the basis for efficient genomic selection of animals that are less susceptible to serious eye diseases.     

Linkage disequilibrium and association of MAPT H1 in Parkinson disease

The MAPT H1 haplotype has been associated with four-repeat (4R) tauopathies, including progressive supranuclear palsy, corticobasal degeneration, and argyrophilic grain disease. More controversial is that the same haplotype has been associated with Parkinson disease (PD). Using H1-specific single-nucleotide polymorphisms, we demonstrate that MAPT H1 is a misnomer and consists of a family of recombining H1 alleles. Population genetics, linkage disequilibrium, and association analyses have shown that specific MAPT H1 subhaplotypes are preferentially associated with Parkinson disease. Using a sliding scale of MAPT H1-specific haplotypes--in age/sex-matched PD cases and controls from central Norway--we have refined the disease association to within an approximately 90-kb interval of the 5' end of the MAPT locus.     

Photosynthesis-dependent anthocyanin pigmentation in arabidopsis

Light is the ultimate energy source for photo-autotrophs on earth. For green plants, however, it can also be toxic under certain stressful environmental conditions and at critical developmental stages. Anthocyanins, a class of flavonoids, act as an effective screening mechanism that allows plant survival and proliferation under occasional periods of harmful irradiation through modulation of light absorption. Apart from light-sensing through photoreceptors such as phytochrome and cryptochrome, plants use the photosynthetic electron transfer (PET) chain to integrate light information. The redox status of the plastoquinone (PQ) pool of the PET chain regulates anthocyanin biosynthesis genes, together with the plant hormone ethylene and plant hormone-like sugars. A complex signaling apparatus in acyanic cells appears to transduce information to cyanic cells to regulate anthocyanin production through an intercellular signaling pathway that remains largely uncharacterized. This review will highlight recent advances in this field and their implications for the regulation of anthocyanin pigmentation.Key words: anthocyanin induction, ethylene, sugar, light, photosynthesis, mesophyll-derived signalLight is the key stimulus for anthocyanin biosynthesis among numerous other environmental cues such as temperature, nutrient deficiency, water status, wounding and pathogen attack.¹ The production of anthocyanin in young seedlings requires prolonged exposure to visible and near-visible wavelengths of light at a relatively high photon flux, and the extent of the plant response to light is a function of light quality and quantity.² High-light conditions trigger the accumulation of anthocyanin in vegetative tissues, which serves as a means to safeguard against the detrimental effects of excess light on the photosynthetic apparatus, which can lead to photo-inhibition. Sugar is a common regulator of a number of genes involved in photosynthesis, carbohydrate metabolism and pathogenesis. It also induces anthocyanin biosynthesis in Arabidopsis seedlings in the form of disaccharide sugars such as sucrose (Suc) and maltose.^3–5 Plant hormones such as abscisic acid, jasmonic acid, cytokinin and gibberellic acid act in concert with sugar in the presence of light to regulate anthocyanin accumulation in either a positive or negative manner.⁶ Thus, light, sugar and hormone signals interact in an intricate signaling network that simultaneously coordinates plant homeostasis and regulates anthocyanin pigmentation. Here, we review recent advances in our understanding of these interactions between light, sugar and ethylene and how they regulate anthocyanin pigmentation in Arabidopsis.     

Linkage disequilibrium analysis for microsatellite loci in six cattle breeds

Autosomal microsatellites are valuable tools for investigating genetic diversity and population structure and making conservation decisions to preserve valuable breeds of domestic animals. We carried out a linkage disequilibrium analysis using 29 microsatellite markers in six cattle populations: Suksun, Istoben, Yaroslavl, Kholmogory, Grey Ukrainian and Pechora type of Khologory cattle. We discovered a significant linkage disequilibrium between microsatellites INRA037 and CSRM60 in Grey Ukrainian cattle.     

Redundancy analysis,genome-wide association studies and the pigmentation of brown trout (Salmo trutta L.)

The association of molecular variants with phenotypic variation is a main issue in biology, often tackled with genome-wide association studies (GWAS). GWAS are challenging, with increasing, but still limited, use in evolutionary biology. We used redundancy analysis (RDA) as a complimentary ordination approach to single- and multitrait GWAS to explore the molecular basis of pigmentation variation in brown trout (Salmo trutta) belonging to wild populations impacted by hatchery fish. Based on 75,684 single nucleotide polymorphic (SNP) markers, RDA, single- and multitrait GWAS allowed the extraction of 337 independent colour patterning loci (CPLs) associated with trout pigmentation traits, such as the number of red and black spots on flanks. Collectively, these CPLs (i) mapped onto 35 out of 40 brown trout linkage groups indicating a polygenic genomic architecture of pigmentation, (ii) were found to be associated with 218 candidate genes, including 197 genes formerly mentioned in the literature associated to skin pigmentation, skin patterning, differentiation or structure notably in a close relative, the rainbow trout (Onchorhynchus mykiss), and (iii) related to functions relevant to pigmentation variation (e.g., calcium- and ion-binding, cell adhesion). Annotated CPLs include genes with well-known pigmentation effects (e.g., PMEL, SLC45A2, SOX10), but also markers associated with genes formerly found expressed in rainbow or brown trout skins. RDA was also shown to be useful to investigate management issues, especially the dynamics of trout pigmentation submitted to several generations of hatchery introgression.     

Current opportunities and challenges: genome-wide association studies on pigmentation and skin cancer

Genome-wide association studies (GWAS) have become a widely used approach for genetic association studies of various human traits. A few GWAS have been conducted with the goal of identifying novel loci for pigmentation traits, melanoma, and non-melanoma skin cancer. Nevertheless, the phenotype variation explained by the genetic markers identified so far is limited. In this review, we discuss the GWAS study design and its application in pigmentation and skin cancer research. Furthermore, we summarize recent developments in post-GWAS activities such as meta-analysis, pathway analysis, and risk prediction.     

Linkage disequilibrium and haplotype analysis in German Friedreich ataxia families

The main mutation causing Friedreich ataxia (FRDA) is the expansion of a GAA repeat localized within the intron between exon 1 and exon 2 of the gene X25. This expansion has been observed in 98% of FRDA chromosomes. To analyze frequencies of markers tightly linked to the Friedreich ataxia gene and to investigate wheter a limited number of ancestral chromosomes are shared by German FRDA families, a detailed analysis employing nine polymorphic markers was performed. We found strong linkage disequilibria and association of FRDA expansions with a few haplotypes. FRDA haplotypes differ significantly from control haplotypes. Our results confirm that GAA repeat expansions in intron 1 of the frataxin gene are limited to a few chromosomes and indicate an obvious founder effect in German patients. Based on these analyses, we estimate a minimum age of the mutation of 107 generations.     

Linkage disequilibrium analysis of allelic heterogeneity in DNA methylation

Heterogeneity of DNA methylation status among alleles is observed in various cell types and is involved in epigenetic gene regulation and cancer biology. However, the individual methylation profile within each allele has not yet been examined at the whole-genome level. In the present study, we applied linkage disequilibrium analysis to the DNA methylation data obtained from whole-genome bisulfite sequencing studies in mouse germline and other types of cells. We found that the methylation status of 2 consecutive CpG sites showed deviation from equilibrium frequency toward concordant linkage (both methylated or both unmethylated) in germline cells. In the imprinting loci where methylation of constituent alleles is known, our analysis detected the deviation toward the concordant linkage as expected. In addition, we applied this analysis to the transitional zone between methylated and unmethylated regions and to the cells undergoing epigenetic reprogramming. In both cases, deviation to the concordant-linked alleles was conspicuous, indicating that the methylation pattern is not random but rather concordant within each allele. These results will provide the key to understanding the mechanism underlying allelic heterogeneity.     

Linkage disequilibrium for different scales and applications

Assessing the patterns of linkage disequilibrium (LD) has become an important issue in both evolutionary biology and medical genetics since the rapid accumulation of densely spaced DNA sequence variation data in several organisms. LD deals with the correlation of genetic variation at two or more loci or sites in the genome within a given population. There are a variety of LD measures which range from traditional pairwise LD measures such as D' or r2 to entropy-based multi-locus measures or haplotype-specific approaches. Understanding the evolutionary forces (in particular recombination) that generate the observed variation of LD patterns across genomic regions is addressed by model-based LD analysis. Marker type and its allelic composition also influence the observed LD pattern, microsatellites having a greater power to detect LD in population isolates than SNPs. This review aims to explain basic LD measures and their application properties.     

Linkage disequilibrium and association studies in higher plants: Present status and future prospects

During the last two decades, DNA-based molecular markers have been extensively utilized for a variety of studies in both plant and animal systems. One of the major uses of these markers is the construction of genome-wide molecular maps and the genetic analysis of simple and complex traits. However, these studies are generally based on linkage analysis in mapping populations, thus placing serious limitations in using molecular markers for genetic analysis in a variety of plant systems. Therefore, alternative approaches have been suggested, and one of these approaches makes use of linkage disequilibrium (LD)-based association analysis. Although this approach of association analysis has already been used for studies on genetics of complex traits (including different diseases) in humans, its use in plants has just started. In the present review, we first define and distinguish between LD and association mapping, and then briefly describe various measures of LD and the two methods of its depiction. We then give a list of different factors that affect LD without discussing them, and also discuss the current issues of LD research in plants. Later, we also describe the various uses of LD in plant genomics research and summarize the present status of LD research in different plant genomes. In the end, we discuss briefly the future prospects of LD research in plants, and give a list of softwares that are useful in LD research, which is available as electronic supplementary material (ESM) Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

Joint analysis for genome-wide association studies in family-based designs

In family-based data, association information can be partitioned into the between-family information and the within-family information. Based on this observation, Steen et al. (Nature Genetics. 2005, 683-691) proposed an interesting two-stage test for genome-wide association (GWA) studies under family-based designs which performs genomic screening and replication using the same data set. In the first stage, a screening test based on the between-family information is used to select markers. In the second stage, an association test based on the within-family information is used to test association at the selected markers. However, we learn from the results of case-control studies (Skol et al. Nature Genetics. 2006, 209-213) that this two-stage approach may be not optimal. In this article, we propose a novel two-stage joint analysis for GWA studies under family-based designs. For this joint analysis, we first propose a new screening test that is based on the between-family information and is robust to population stratification. This new screening test is used in the first stage to select markers. Then, a joint test that combines the between-family information and within-family information is used in the second stage to test association at the selected markers. By extensive simulation studies, we demonstrate that the joint analysis always results in increased power to detect genetic association and is robust to population stratification.     

Linkage disequilibrium in Bougainville Island

Linkage disequilibria are estimated for three 2-locus systems in 18 samples from Bougainville Island, Solomon Islands. The systems are haptoglobin, acid phosphatase and MN blood group. The disequilibria are estimated two ways: by maximum likelihood (ML) and by the covariance between the non-alleles. Though seven of the 52 ML estimates are statistically different than zero, none of the covariance estimates are significant. We conclude that because linkage disequilibrium for loosely linked loci is a small quantity and because the sample sizes for most populations studied by anthropologists are small, linkage disequilibrium will not be a useful parameter for the study of natural selection in these populations.     

Linkage disequilibrium and gametophytic self-incompatibility

Summary The approach to linkage equilibrium of a locus linked to the locus determining gametophytic self-incompatibility (S) is considered. For the simplest case of three alleles at the S locus and two at the linked locus it is necessary to consider 3 measures of linkage disequilibrium. These are found to approach their equilibrium value of zero in one of three ways: 1) steadily declining to zero; 2) oscillating as decline proceeds; 3) a combination: 2) followed by 1). Linkage equilibrium may be established before genotype frequencies reach their expectation under random crossing. Earlier studies (Li 1951; Moran 1962) of the approach to S allele equilibrium have been based on the assumption that all types of pollen take part in fertilizations equally frequently. Such an assumption leads to simpler expressions for changes in S gene frequencies but is extremely unrealistic and, in particular, leads to a different rate of approach to equilibrium from the more comprehensive model. It is shown that even in the absence of selection it is not possible to predict the equilibrium gene frequency of a linked locus until S allele equilibrium is reached. This frequency may be either higher or lower than that calculated from a gene count in the starting genotype pool. However, these two gene frequencies may stabilize long before linkage equilibrium is achieved. An examination of selection against one genotype at the linked locus is undertaken. If linkage is complete, lethality can be less effective at reducing the gene frequency than is less intense selection (in only a few generations of selection). Here too linkage equilibrium may be established with selection still effective in bringing about a decline in gene frequency. An examination of the analysis and conclusions of Rasmuson (1980) shows that because these were based on the inadequate formulae previously discussed and exclude phenomena discussed above, they are misleading. The possibility of a gametophytic self-incompatibility system providing a sufficient condition for the sheltering of lethals in the absence of the condition of complete linkage to the S locus (r=0) is shown to be unlikely.     

SNP-based pathway enrichment analysis for genome-wide association studies

Background  

Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS) to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs), have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs.     

Linkage disequilibrium maps constructed with common SNPs are useful for first-pass disease association screens

To develop an efficient strategy for mapping genetic factors associated with common diseases, we constructed linkage disequilibrium (LD) maps of human chromosomes 5, 7, 17, and X. These maps consist of common single nucleotide polymorphisms at an average intermarker distance of 100 kb. The genotype data from these markers in a panel of American samples of European descent were analyzed to produce blocks of markers in strong pair-wise LD. Power calculations were used to guide block definitions and predicted that high-level LD maps would be useful in initial genome scans for susceptibility alleles in case-control association studies of complex diseases. As anticipated, LD blocks on the X chromosome were larger and covered more of the chromosome than those found on the autosomes.     

Linkage disequilibrium in domestic sheep

The last decade has seen a dramatic increase in the number of livestock QTL mapping studies. The next challenge awaiting livestock geneticists is to determine the actual genes responsible for variation of economically important traits. With the advent of high density single nucleotide polymorphism (SNP) maps, it may be possible to fine map genes by exploiting linkage disequilibrium between genes of interest and adjacent markers. However, the extent of linkage disequilibrium (LD) is generally unknown for livestock populations. In this article microsatellite genotype data are used to assess the extent of LD in two populations of domestic sheep. High levels of LD were found to extend for tens of centimorgans and declined as a function of marker distance. However, LD was also frequently observed between unlinked markers. The prospects for LD mapping in livestock appear encouraging provided that type I error can be minimized. Properties of the multiallelic LD coefficient D' were also explored. D' was found to be significantly related to marker heterozygosity, although the relationship did not appear to unduly influence the overall conclusions. Of potentially greater concern was the observation that D' may be skewed when rare alleles are present. It is recommended that the statistical significance of LD is used in conjunction with coefficients such as D' to determine the true extent of LD.