A genome-wide association study for quantitative trait loci of show-jumping in Hanoverian warmblood horses

Show-jumping is an economically important breeding goal in Hanoverian warmblood horses. The aim of this study was a genome-wide association study (GWAS) for quantitative trait loci (QTL) for show-jumping in Hanoverian warmblood horses, employing the Illumina equine SNP50 Beadchip. For our analyses, we genotyped 115 stallions of the National State stud of Lower Saxony. The show-jumping talent of a horse includes style and ability in free-jumping. To control spurious associations based on population stratification, two different mixed linear animal model (MLM) approaches were employed, besides linear models with fixed effects only and adaptive permutations for correcting multiple testing. Population stratification was explained best in the MLM considering Hanoverian, Thoroughbred, Trakehner and Holsteiner genes and the marker identity-by-state relationship matrix. We identified six QTL for show-jumping on horse chromosomes (ECA) 1, 8, 9 and 26 (-log(10) P-value >5) and further putative QTL with -log(10) P-values of 3-5 on ECA1, 3, 11, 17 and 21. Within six QTL regions, we identified human performance-related genes including PAPSS2 on ECA1, MYL2 on ECA8, TRHR on ECA9 and GABPA on ECA26 and within the putative QTL regions NRAP on ECA1, and TBX4 on ECA11. The results of our GWAS suggest that genes involved in muscle structure, development and metabolism are crucial for elite show-jumping performance. Further studies are required to validate these QTL in larger data sets and further horse populations.     

A genome-wide association analysis of quantitative trait loci for protein fraction content in Tibetan wild barley

The genetic associations and differences of four protein fractions were investigated in Tibetan wild barley. Albumin, globulin and hordein contents were under genetic control probably via multiple genes/quantitative trait loci. A correlation analysis showed that globulin was significantly associated with albumin, glutelin and hordein, while hordein was closely correlated with glutelin. Forty-nine diversity array technology (DArT) markers, which were distributed over seven chromosomes, were associated with the protein fraction contents. Those DArT markers associated with hordein were the same as those associated with globulin and glutelin. Only five markers associated with hordein, globulin and glutelin were also associated with albumin. Most of the protein fraction contents are therefore controlled by same genes which may contribute to total protein content. The discovery of new markers associated with specific protein fractions could be used to detect genes controlling protein content in the barley germplasm.     

A genome-wide association study of psoriasis and psoriatic arthritis identifies new disease loci

A genome-wide association study was performed to identify genetic factors involved in susceptibility to psoriasis (PS) and psoriatic arthritis (PSA), inflammatory diseases of the skin and joints in humans. 223 PS cases (including 91 with PSA) were genotyped with 311,398 single nucleotide polymorphisms (SNPs), and results were compared with those from 519 Northern European controls. Replications were performed with an independent cohort of 577 PS cases and 737 controls from the U.S., and 576 PSA patients and 480 controls from the U.K.. Strongest associations were with the class I region of the major histocompatibility complex (MHC). The most highly associated SNP was rs10484554, which lies 34.7 kb upstream from HLA-C (P = 7.8x10(-11), GWA scan; P = 1.8x10(-30), replication; P = 1.8x10(-39), combined; U.K. PSA: P = 6.9x10(-11)). However, rs2395029 encoding the G2V polymorphism within the class I gene HCP5 (combined P = 2.13x10(-26) in U.S. cases) yielded the highest ORs with both PS and PSA (4.1 and 3.2 respectively). This variant is associated with low viral set point following HIV infection and its effect is independent of rs10484554. We replicated the previously reported association with interleukin 23 receptor and interleukin 12B (IL12B) polymorphisms in PS and PSA cohorts (IL23R: rs11209026, U.S. PS, P = 1.4x10(-4); U.K. PSA: P = 8.0x10(-4); IL12B:rs6887695, U.S. PS, P = 5x10(-5) and U.K. PSA, P = 1.3x10(-3)) and detected an independent association in the IL23R region with a SNP 4 kb upstream from IL12RB2 (P = 0.001). Novel associations replicated in the U.S. PS cohort included the region harboring lipoma HMGIC fusion partner (LHFP) and conserved oligomeric golgi complex component 6 (COG6) genes on chromosome 13q13 (combined P = 2x10(-6) for rs7993214; OR = 0.71), the late cornified envelope gene cluster (LCE) from the Epidermal Differentiation Complex (PSORS4) (combined P = 6.2x10(-5) for rs6701216; OR 1.45) and a region of LD at 15q21 (combined P = 2.9x10(-5) for rs3803369; OR = 1.43). This region is of interest because it harbors ubiquitin-specific protease-8 whose processed pseudogene lies upstream from HLA-C. This region of 15q21 also harbors the gene for SPPL2A (signal peptide peptidase like 2a) which activates tumor necrosis factor alpha by cleavage, triggering the expression of IL12 in human dendritic cells. We also identified a novel PSA (and potentially PS) locus on chromosome 4q27. This region harbors the interleukin 2 (IL2) and interleukin 21 (IL21) genes and was recently shown to be associated with four autoimmune diseases (Celiac disease, Type 1 diabetes, Grave's disease and Rheumatoid Arthritis).     

A genome-wide association study of facial morphology identifies novel genetic loci in Han Chinese

The human face is a heritable surface with many complex sensory organs. In recent years, many genetic loci associated with facial features have been reported in different populations, yet there is a lack of studies on the Han Chinese population. Here, we report a genome-wide association study of 3 D normal human faces of 2,659 Han Chinese with autosegment phenotypes of facial morphology. We identify singlenucleotide polymorphisms(SNPs) encompassing four genomic regions showing significant associations with different facial regions, including SNPs in DENND1 B associated with the chin, SNPs among PISRT1 associated with eyes, SNPs between DCHS2 and SFRP2 associated with the nose, and SNPs in VPS13 B associated with the nose. We replicate 24 SNPs from previously reported genetic loci in different populations, whose candidate genes are DCHS2, SUPT3 H, HOXD1, SOX9, PAX3, and EDAR. These results provide a more comprehensive understanding of the genetic basis of variation in human facial morphology.     

Genome-wide association study identifies quantitative trait loci regions involved in muscle acidic profile in Large White heavy pigs

The widespread use of genome-wide association studies resulted in the discovery of genomic regions associated with fatty acid (FA) composition in different porcine tissues, but little information exists about the genes involved in FA composition of meat obtained from heavy pigs selected for the production of Italian dry-cured hams. To this objective, we genotyped with a single nucleotide polymorphism (SNP) panel 795 Italian Large White heavy pigs to identify the markers and genomic regions associated with Semimembranosus muscle FA profile. Heritability estimates for intramuscular fat FA profile were of low-to-moderate magnitude, suggesting that these traits may be improved with genomic selection. On the whole, 45 SNPs were significantly associated with 14 FAs, and 4 of them (ALGA008109, ALGA0081097, CASI0010164 and SIRI0000267) were associated with more than 1 FA. The palmitoleic : palmitic and oleic : stearic ratios displayed the highest number of significant markers and the most significant associations (Bonferroni adjusted P < 5.00E−07). Of particular interest, the palmitoleic : palmitic ratio was strongly associated with markers located at 111 to 114 Mb on chromosome 14, in the same chromosomal region where Stearoyl-CoA desaturase Δ9 (SCD) gene is located. Several significant chromosomal regions were found; some of them harbour key genes playing pivotal roles in FA desaturation and elongation, such as SCD and some members of the Elongation of Very Long-Chain FA (ELOVL) gene family. The results suggest that the identification of causal mutations in these regions may provide a set of markers useful for selection schemes aimed at improving FA composition in pork products.     

Bayesian model selection for genome-wide epistatic quantitative trait loci analysis

The problem of identifying complex epistatic quantitative trait loci (QTL) across the entire genome continues to be a formidable challenge for geneticists. The complexity of genome-wide epistatic analysis results mainly from the number of QTL being unknown and the number of possible epistatic effects being huge. In this article, we use a composite model space approach to develop a Bayesian model selection framework for identifying epistatic QTL for complex traits in experimental crosses from two inbred lines. By placing a liberal constraint on the upper bound of the number of detectable QTL we restrict attention to models of fixed dimension, greatly simplifying calculations. Indicators specify which main and epistatic effects of putative QTL are included. We detail how to use prior knowledge to bound the number of detectable QTL and to specify prior distributions for indicators of genetic effects. We develop a computationally efficient Markov chain Monte Carlo (MCMC) algorithm using the Gibbs sampler and Metropolis-Hastings algorithm to explore the posterior distribution. We illustrate the proposed method by detecting new epistatic QTL for obesity in a backcross of CAST/Ei mice onto M16i.     

A next generation sequencing combined genome-wide association study identifies novel tuberculosis susceptibility loci in Chinese population

The genetic factors of tuberculosis (TB) susceptibility have been widely recognized. Here we performed a two-stage study in 616 TB patients and 709 healthy controls to systematically identify the genetic markers of TB susceptibility. In the discovery stage, we identified 93 single nucleotide polymorphisms (SNPs) and 3 human leucocyte antigen (HLA) class II alleles that had potential associations with TB susceptibility. In the validation stage, we confirmed that 6 nominally significant SNPs, including 2 novel missense variants at RAB17 and DCTN4 (odds ratio (OR) = 1.40, P = 4.98 × 10⁻³ and OR = 2.30, P = 3.17 × 10⁻² respectively), were associated with the predisposition to TB. Moreover, our study found that HLA-II allele DQA1*05:05 (P = 0.0011, OR = 1.44, 95%CI = 1.15–1.77) was a TB susceptibility locus for the first time. This study comprehensively investigated the genetic variants that were associated with TB susceptibility and provided insight into the tuberculosis pathogenesis.     

Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies

Background

The apparent effect of a single nucleotide polymorphism (SNP) on phenotype depends on the linkage disequilibrium (LD) between the SNP and a quantitative trait locus (QTL). However, the phase of LD between a SNP and a QTL may differ between Bos indicus and Bos taurus because they diverged at least one hundred thousand years ago. Here, we test the hypothesis that the apparent effect of a SNP on a quantitative trait depends on whether the SNP allele is inherited from a Bos taurus or Bos indicus ancestor.

Methods

Phenotype data on one or more traits and SNP genotype data for 10 181 cattle from Bos taurus, Bos indicus and composite breeds were used. All animals had genotypes for 729 068 SNPs (real or imputed). Chromosome segments were classified as originating from B. indicus or B. taurus on the basis of the haplotype of SNP alleles they contained. Consequently, SNP alleles were classified according to their sub-species origin. Three models were used for the association study: (1) conventional GWAS (genome-wide association study), fitting a single SNP effect regardless of subspecies origin, (2) interaction GWAS, fitting an interaction between SNP and subspecies-origin, and (3) best variable GWAS, fitting the most significant combination of SNP and sub-species origin.

Results

Fitting an interaction between SNP and subspecies origin resulted in more significant SNPs (i.e. more power) than a conventional GWAS. Thus, the effect of a SNP depends on the subspecies that the allele originates from. Also, most QTL segregated in only one subspecies, suggesting that many mutations that affect the traits studied occurred after divergence of the subspecies or the mutation became fixed or was lost in one of the subspecies.

Conclusions

The results imply that GWAS and genomic selection could gain power by distinguishing SNP alleles based on their subspecies origin, and that only few QTL segregate in both B. indicus and B. taurus cattle. Thus, the QTL that segregate in current populations likely resulted from mutations that occurred in one of the subspecies and can have both positive and negative effects on the traits. There was no evidence that selection has increased the frequency of alleles that increase body weight.     

A statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci

Non-equivalent expression of alleles at a locus results in genomic imprinting. In this article, a statistical framework for genome-wide scanning and testing of imprinted quantitative trait loci (iQTL) underlying complex traits is developed based on experimental crosses of inbred line species in backcross populations. The joint likelihood function is composed of four component likelihood functions with each of them derived from one of four backcross families. The proposed approach models genomic imprinting effect as a probability measure with which one can test the degree of imprinting. Simulation results show that the model is robust for identifying iQTL with various degree of imprinting ranging from no imprinting, partial imprinting to complete imprinting. Under various simulation scenarios, the proposed model shows consistent parameter estimation with reasonable precision and high power in testing iQTL. When a QTL shows Mendelian effect, the proposed model also outperforms traditional Mendelian model. Extension to incorporate maternal effect is also given. The developed model, built within the maximum likelihood framework and implemented with the EM algorithm, provides a quantitative framework for testing and estimating iQTL involved in the genetic control of complex traits.     

Genome‐wide association analysis identifies quantitative trait loci for growth in a Landrace purebred population

Growth‐related traits are complex and economically important in the livestock industry. The aim of this study was to identify quantitative trait loci (QTL) and the associated positional candidate genes affecting growth in pigs. A genome‐wide association study (GWAS) was performed using the porcine single‐nucleotide polymorphism (SNP) 60K bead chip. A mixed‐effects model and linear regression approach were used for the GWAS. The data used in the study included 490 purebred Landrace pigs. All experimental animals were genotyped with 39 438 SNPs located throughout the pig autosomes. We identified a strong association between a SNP marker on chromosome 16 and body weight at 71 days of age (ALGA0092396, P = 5.35 × 10^?9, Bonferroni adjusted P < 0.05). The SNP marker was located near the genomic region containing IRX4, which encodes iroquois homeobox 4. This SNP marker could be useful in the selective breeding program after validating its effect on other populations.     

Rapid and robust resampling-based multiple-testing correction with application in a genome-wide expression quantitative trait loci study

Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. In a typical eQTL study, the huge number of genetic markers and expression traits and their complicated correlations present a challenging multiple-testing correction problem. The resampling-based test using permutation or bootstrap procedures is a standard approach to address the multiple-testing problem in eQTL studies. A brute force application of the resampling-based test to large-scale eQTL data sets is often computationally infeasible. Several computationally efficient methods have been proposed to calculate approximate resampling-based P-values. However, these methods rely on certain assumptions about the correlation structure of the genetic markers, which may not be valid for certain studies. We propose a novel algorithm, rapid and exact multiple testing correction by resampling (REM), to address this challenge. REM calculates the exact resampling-based P-values in a computationally efficient manner. The computational advantage of REM lies in its strategy of pruning the search space by skipping genetic markers whose upper bounds on test statistics are small. REM does not rely on any assumption about the correlation structure of the genetic markers. It can be applied to a variety of resampling-based multiple-testing correction methods including permutation and bootstrap methods. We evaluate REM on three eQTL data sets (yeast, inbred mouse, and human rare variants) and show that it achieves accurate resampling-based P-value estimation with much less computational cost than existing methods. The software is available at http://csbio.unc.edu/eQTL.     

Web-based genome-wide association study identifies two novel loci and a substantial genetic component for Parkinson's disease

Although the causes of Parkinson's disease (PD) are thought to be primarily environmental, recent studies suggest that a number of genes influence susceptibility. Using targeted case recruitment and online survey instruments, we conducted the largest case-control genome-wide association study (GWAS) of PD based on a single collection of individuals to date (3,426 cases and 29,624 controls). We discovered two novel, genome-wide significant associations with PD-rs6812193 near SCARB2 (p = 7.6 × 10(-10), OR = 0.84) and rs11868035 near SREBF1/RAI1 (p = 5.6 × 10(-8), OR = 0.85)-both replicated in an independent cohort. We also replicated 20 previously discovered genetic associations (including LRRK2, GBA, SNCA, MAPT, GAK, and the HLA region), providing support for our novel study design. Relying on a recently proposed method based on genome-wide sharing estimates between distantly related individuals, we estimated the heritability of PD to be at least 0.27. Finally, using sparse regression techniques, we constructed predictive models that account for 6%-7% of the total variance in liability and that suggest the presence of true associations just beyond genome-wide significance, as confirmed through both internal and external cross-validation. These results indicate a substantial, but by no means total, contribution of genetics underlying susceptibility to both early-onset and late-onset PD, suggesting that, despite the novel associations discovered here and elsewhere, the majority of the genetic component for Parkinson's disease remains to be discovered.     

A genome-wide association study identifies 5 loci associated with frozen shoulder and implicates diabetes as a causal risk factor

Frozen shoulder is a painful condition that often requires surgery and affects up to 5% of individuals aged 40–60 years. Little is known about the causes of the condition, but diabetes is a strong risk factor. To begin to understand the biological mechanisms involved, we aimed to identify genetic variants associated with frozen shoulder and to use Mendelian randomization to test the causal role of diabetes. We performed a genome-wide association study (GWAS) of frozen shoulder in the UK Biobank using data from 10,104 cases identified from inpatient, surgical and primary care codes. We used data from FinnGen for replication and meta-analysis. We used one-sample and two-sample Mendelian randomization approaches to test for a causal association of diabetes with frozen shoulder. We identified five genome-wide significant loci. The most significant locus (lead SNP rs28971325; OR = 1.20, [95% CI: 1.16–1.24], p = 5x10^-29) contained WNT7B. This variant was also associated with Dupuytren’s disease (OR = 2.31 [2.24, 2.39], p<1x10^-300) as were a further two of the frozen shoulder associated variants. The Mendelian randomization results provided evidence that type 1 diabetes is a causal risk factor for frozen shoulder (OR = 1.03 [1.02–1.05], p = 3x10^-6). There was no evidence that obesity was causally associated with frozen shoulder, suggesting that diabetes influences risk of the condition through glycemic rather than mechanical effects. We have identified genetic loci associated with frozen shoulder. There is a large overlap with Dupuytren’s disease associated loci. Diabetes is a likely causal risk factor. Our results provide evidence of biological mechanisms involved in this common painful condition.     

Efficient association mapping of quantitative trait loci with selective genotyping

Selective genotyping (i.e., genotyping only those individuals with extreme phenotypes) can greatly improve the power to detect and map quantitative trait loci in genetic association studies. Because selection depends on the phenotype, the resulting data cannot be properly analyzed by standard statistical methods. We provide appropriate likelihoods for assessing the effects of genotypes and haplotypes on quantitative traits under selective-genotyping designs. We demonstrate that the likelihood-based methods are highly effective in identifying causal variants and are substantially more powerful than existing methods.     

Application of genome-wide SNP data for uncovering pairwise relationships and quantitative trait loci

The genetic analysis of quantitative traits in humans is changing as a result of the availability of whole-genome SNP data. Heritability analysis can make use of actual genetic sharing between pairs of individuals estimated from the genotype data, rather than the expected genetic sharing implied by their family relationship. This could provide more accurate heritability estimates and help to overcome the equal environment assumption. Quantitative trait locus (QTL) linkage mapping can make use of local genetic sharing inferred from very dense local genotype data from pedigree members or individuals not previously known to be related. This approach may be particularly suited for detecting loci that contain rare variants with major effect on the phenotype. Finally, whole-genome SNP data can be used to measure the genetic similarity between individuals to provide matched sets for association studies, in order to avoid spurious association from population stratification.     

A genomewide scan for intelligence identifies quantitative trait loci on 2q and 6p

Between 40% and 80% of the variation in human intelligence (IQ) is attributable to genetic factors. Except for many rare mutations resulting in severe cognitive dysfunction, attempts to identify these factors have not been successful. We report a genomewide linkage scan involving 634 sibling pairs designed to identify chromosomal regions that explain variation in IQ. Model-free multipoint linkage analysis revealed evidence of a significant quantitative-trait locus for performance IQ at 2q24.1-31.1 (LOD score 4.42), which overlaps the 2q21-33 region that has repeatedly shown linkage to autism. A second region revealed suggestive linkage for both full-scale and verbal IQs on 6p25.3-22.3 (LOD score 3.20 for full-scale IQ and 2.33 for verbal IQ), overlapping marginally with the 6p22.3-21.31 region implicated in reading disability and dyslexia.     

Genome-wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12

Reproductive performance is a critical trait in dairy cattle. Poor reproductive performance leads to prolonged calving intervals, higher culling rates and extra expenses related to multiple inseminations, veterinary treatments and replacements. Genetic gain for improved reproduction through traditional selection is often slow because of low heritability and negative correlations with production traits. Detection of DNA markers associated with improved reproductive performance through genome-wide association studies could lead to genetic gain that is more balanced between fertility and production. Norwegian Red cattle are well suited for such studies, as very large numbers of detailed reproduction records are available. We conducted a genome-wide association study for non-return rate, fertility treatments and retained placenta using almost 1 million records on these traits and 17 343 genome-wide single-nucleotide polymorphisms. Genotyping costs were minimized by genotyping the sires of the cows recorded and by using daughter averages as phenotypes. The genotyped sires were assigned to either a discovery or a validation population. Associations were only considered to be validated if they were significant in both groups. Strong associations were found and validated on chromosomes 1, 5, 8, 9, 11 and 12. Several of these were highly supported by findings in other studies. The most important result was an association for non-return rate in heifers in a region of BTA12 where several associations for milk production traits have previously been found. Subsequent fine-mapping verified the presence of a quantitative trait loci (QTL) having opposing effects on non-return rate and milk production at 18 Mb. The other reproduction QTL did not have pleiotropic effects on milk production, and these are therefore of considerable interest for use in marker-assisted selection.