Correction for multiple testing in a gene region

The relationship of maternal polymorphisms of genes related to meiosis and DNA damage repair with fetal chromosomal stability

OBJECTIVES

To evaluate the association between maternal polymorphisms of NANOS3 rs2016163, HELQ rs4693089, PRIM1 rs2277339, TLK1 rs10183486, ERCC6 rs2228526, EXO1 rs1635501, DMC1 rs5757133, and MSH5 rs2075789 and fetal chromosomal abnormality.

METHODS

This retrospective case-control study included 571 women with fetal chromosome abnormalities (330 pregnant women diagnosed with fetal aneuploidy, 241 with fetal de novo structural chromosome pregnancy) and 811 healthy pregnant women between January 2018 and April 2022. All the above polymorphisms were tested using SNaPshot.

RESULTS

All the eight polymorphisms were analyzed for genotypes, alleles, under dominant and recessive genetic models. Significant distribution differences of TLK1 rs10183486 in fetal chromosome structural abnormality were found between the case group and control subjects who were <35 years of age [Genotype: p=0.029; Dominant: OR (95 %CI)=0.46 (0.25-0.82), p=0.01 and allele: OR (95 %CI)=0.47 (0.27-0.82), p=0.01 respectively], while no difference was found in the recessive model [OR (95 %CI)=2.49 (0.31-20.40), p=0.39]. In advanced age subgroups for fetal aneuploidy, significant differences were found in genotypes analysis of PRIM1 rs2277339 (p=0.008), allele analysis of TLK1 rs10183486 [OR (95 %CI)=0.62 (0.42-0.91), p=0.02]. For the fetal chromosome structural abnormality population, HELQ rs4693089 revealed a significant distribution difference (p=0.01) but not in the allele, dominant and recessive genetic models analysis (p>0.05 individually).

CONCLUSIONS

For older women, maternal PRIM1 rs2277339 and TLK1 rs10183486 polymorphisms may be associated with fetal aneuploidy, while HELQ rs4693089 may be associated with fetal chromosome structural abnormality. Also, carriers of T allele of TLK1 rs10183486 have a lower risk of fetal chromosome structural abnormality in younger women.

Collagen Gene Variants and Anterior Cruciate Ligament Rupture in Italian Athletes: A Preliminary Report

Several studies have investigated the role of genetics in anterior cruciate ligament (ACL) rupture, often returning conflicting results. The present pilot study aimed to analyze the association between six Single Nucleotide Polymorphisms (SNPs) (rs1800012; rs12722; rs13946; rs240736; rs970547; and rs4870723, located on the COL1A1, COL5A1, COL12A1, and COL14A1 genes), and ACL rupture, among Italian athletes. A hypothesis-driven association study was conducted. In total, 181 male and female athletes (n = 86 injured; n = 96 non-injured) were genotyped for the prioritized variants. All polymorphisms were genotyped using PCR RFLP, with the only exception being the rs1800012 on the COL1A1 gene, which was detected using MTPA PCR. The allele frequency distribution fell within the worldwide range. Despite the evident population variability, no selective pressure signals were recorded using PBS analysis. No significant difference was detected between the cases and controls for any of the SNPs (rs1800012; rs13946; rs240736; rs970547, and rs4870723) included in the analyses (p > 0.008, Bonferroni-adjusted for multiple comparisons). Moreover, no significant differences were found when males and females were assessed separately. Further investigations based on a larger sample size are needed, in order to draw solid conclusions for the influence between collagen genes and ACL rupture.

Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle

Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.

Effect of OR51E1 Single Nucleotide Polymorphisms on Glioma Susceptibility in the Chinese Han Population

BACKGROUND

Glioma is one of the common primary intracranial tumors, which is heterogeneous among individuals with a low cure rate. Our study aimed to investigate the association between single nucleotide polymorphisms (SNPs) of the OR51E1 gene and glioma susceptibility in the Chinese Han population.

METHODS

A total of six SNPs on OR51E1 in 1,026 subjects (526 cases and 500 controls) were genotyped by MassARRAY iPLEX GOLD assay. The association between these SNPs and glioma susceptibility was analyzed using logistic regression, and odds ratios (ORs) and 95% confidence intervals (CIs) were also calculated. The multifactor dimensionality reduction (MDR) method was applied to detect "SNP-SNP" interactions.

RESULTS

In the overall sample, polymorphisms rs10768148, rs7102992, and rs10500608 were identified to be associated with glioma risk. In the stratified analysis based on gender, only polymorphism rs10768148 was observed to be associated with the risk of glioma. In the age-stratified analysis, rs7102992, rs74052483, and rs10500609 contributed to the risk of glioma in subjects aged > 40 years. And polymorphisms rs10768148 and rs7102992 were associated with the risk of glioma in subjects aged ≤ 40 years and subjects with astrocytoma. In addition, a strong synergistic relationship between rs74052483 and rs10768148, and a strong redundant relationship between rs7102992 and rs10768148 were identified in the study.

CONCLUSIONS

This study demonstrated the association of OR51E1 polymorphisms with glioma susceptibility, providing a basis for assessing glioma risk-associated variants in the Chinese Han population.

Interactions between the lipidome and genetic and environmental factors in autism

Autism omics research has historically been reductionist and diagnosis centric, with little attention paid to common co-occurring conditions (for example, sleep and feeding disorders) and the complex interplay between molecular profiles and neurodevelopment, genetics, environmental factors and health. Here we explored the plasma lipidome (783 lipid species) in 765 children (485 diagnosed with autism spectrum disorder (ASD)) within the Australian Autism Biobank. We identified lipids associated with ASD diagnosis (n = 8), sleep disturbances (n = 20) and cognitive function (n = 8) and found that long-chain polyunsaturated fatty acids may causally contribute to sleep disturbances mediated by the FADS gene cluster. We explored the interplay of environmental factors with neurodevelopment and the lipidome, finding that sleep disturbances and unhealthy diet have a convergent lipidome profile (with potential mediation by the microbiome) that is also independently associated with poorer adaptive function. In contrast, ASD lipidome differences were accounted for by dietary differences and sleep disturbances. We identified a large chr19p13.2 copy number variant genetic deletion spanning the LDLR gene and two high-confidence ASD genes (ELAVL3 and SMARCA4) in one child with an ASD diagnosis and widespread low-density lipoprotein-related lipidome derangements. Lipidomics captures the complexity of neurodevelopment, as well as the biological effects of conditions that commonly affect quality of life among autistic people.

Kalpra: A kernel approach for longitudinal pathway regression analysis integrating network information with an application to the longitudinal PsyCourse Study

A popular approach to reduce the high dimensionality resulting from genome-wide association studies is to analyze a whole pathway in a single test for association with a phenotype. Kernel machine regression (KMR) is a highly flexible pathway analysis approach. Initially, KMR was developed to analyze a simple phenotype with just one measurement per individual. Recently, however, the investigation into the influence of genomic factors in the development of disease-related phenotypes across time (trajectories) has gained in importance. Thus, novel statistical approaches for KMR analyzing longitudinal data, i.e. several measurements at specific time points per individual are required. For longitudinal pathway analysis, we extend KMR to long-KMR using the estimation equivalence of KMR and linear mixed models. We include additional random effects to correct for the dependence structure. Moreover, within long-KMR we created a topology-based pathway analysis by combining this approach with a kernel including network information of the pathway. Most importantly, long-KMR not only allows for the investigation of the main genetic effect adjusting for time dependencies within an individual, but it also allows to test for the association of the pathway with the longitudinal course of the phenotype in the form of testing the genetic time-interaction effect. The approach is implemented as an R package, kalpra. Our simulation study demonstrates that the power of long-KMR exceeded that of another KMR method previously developed to analyze longitudinal data, while maintaining (slightly conservatively) the type I error. The network kernel improved the performance of long-KMR compared to the linear kernel. Considering different pathway densities, the power of the network kernel decreased with increasing pathway density. We applied long-KMR to cognitive data on executive function (Trail Making Test, part B) from the PsyCourse Study and 17 candidate pathways selected from Reactome. We identified seven nominally significant pathways.

Haem oxygenase-1 and haemopexin gene polymorphisms and the risk of anti-tuberculosis drug-induced hepatotoxicity in China

Objective: To assess whether the risk of anti-tuberculosis drug-induced hepatotoxicity (ATDH) might be influenced by haem oxygenase-1 (HMOX1) and haemopexin (HPX) gene polymorphisms. Methods: A dynamic anti-tuberculosis treatment cohort was constructed, and the 1:4 matched nested case-control study was analysed. Eight single nucleotide polymorphisms (SNPs) of the two genes were selected for genotyping and Bonferroni correction was performed to correct for multiple comparison. Results: Overall, 7.8% of patients developed ATDH. SNP rs1807714 in the HMOX1 gene had decreased effects on the risk of moderate and severe hepatotoxicity under the dominant and additive models, and hepatocellular injury under the additive model. SNP rs2682099 in the HPX gene had increased effects on the risk of moderate and severe hepatotoxicity under the recessive model. However, these associations disappeared after Bonferroni correction. Conclusion: HMOX1 and HPX gene polymorphisms might not be associated with susceptibility to ATDH in the Chinese population.

Variants in clock genes could be associated with lower risk of type 2 diabetes in an elderly Greek population

OBJECTIVES

Recent evidence has linked circadian rhythm dysregulation to an increased risk of metabolic disorders. This study explores a potential association between variation in genes regulating the endogenous circadian timing system (clock genes) and the risk of type 2 diabetes (T2D) in a sample of Greek elderly people.

STUDY DESIGN

Variants within and upstream or downstream of PPARA, PPARD, CLOCK/TMEM165, PER1, PER2 and PER3 genes were genotyped in 716 individuals with T2D (A) and 569 normoglycemic controls (B), and allele frequencies were compared between the groups in a case control study design.

MAIN OUTCOME MEASURES

Samples were genotyped on Illumina Human PsychArray. Permutation test analysis was implemented to determine statistical significance. To avoid the possibility of subjects with prediabetes being included in the control group, people with HbA1c <5.7% and fasting glucose <100 mg/dl comprised group C (n = 393), for whom a separate analysis was performed (secondary analysis).

RESULTS

A protective role against T2D was identified for 14 variants in the PPARA gene. The rs7291444, rs36125344, rs6008384 in PKDREJ, located upstream of PPARA, and rs2859389 in UTS2, located upstream of PER3, demonstrated a protective role against T2D in both analyses. In contrast, rs6744132, located between HES6 and PER2, was positively correlated with T2D risk. Only in the secondary analysis, rs2278637 in VAMP2, located downstream of PER1, and rs11943456 in CLOCK/TMEM165 were found to confer protection against T2D. In a recessive model analysis of all groups, PPARD variants exhibited a protective role against disease.

CONCLUSIONS

Our findings suggest a possible implication of clock genes in T2D susceptibility. Further studies are needed to clarify the mechanisms that connect circadian rhythm dysfunction and T2D pathogenesis.

Response to Sodium Channel blocking Antiseizure medications and coding polymorphisms of Sodium Channel genes in Taiwanese epilepsy patients

Background

Many antiseizure medications (ASMs) control seizures by blocking voltage-dependent sodium channels. Polymorphisms of sodium channel genes may affect the response to ASMs due to altering the effect of ASMs on blocking sodium channels.

Methods

We conducted a retrospective study of epilepsy patients followed up at the Neurological Department of Kaohsiung Chang Gung Memorial Hospital, Taiwan between January 2010 and December 2018. We categorized the patients into response, partial response, and failure to sodium channel blocking ASM groups. Sodium channel blocking ASMs included phenytoin, carbamazepine, lamotrigine, oxcarbazepine, lacosamide, zonisamide, topiramate, and valproic acid. A subgroup of predominant sodium channel blocking ASMs included phenytoin, carbamazepine, lamotrigine, oxcarbazepine, and lacosamide. Associations between the response of ASMs and single-nucleotide polymorphisms of SCN1A, SCN1B, SCN2A, and SCN9A were analyzed.

Results

Two hundred Taiwanese patients and 21 single-nucleotide polymorphisms among SCN1A, SCN1B, SCN2A, and SCN9A were evaluated. We found allele C of rs55742440 in SCN1B was statistically significantly associated with not achieving seizure-free with sodium channel blocking ASMs. For the predominant sodium channel blocking ASMs group, no SNPs were associated with the response of ASMs.

Conclusion

Single-nucleotide polymorphism in SCN1B was associated with the response to sodium channel blocking ASMs. This highlights the possibility that beta subunits may affect the function of sodium channels and resulted in different responsiveness to ASMs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02395-2.

Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3047 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1426 individuals with PTSD and 1621 controls (2174 males/873 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohen's d = -0.11, p = 0.0055). The tapetum connects the left and right hippocampus, for which structure and function have been consistently implicated in PTSD. Results were consistent even after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

GWAS significance thresholds for deep phenotyping studies can depend upon minor allele frequencies and sample size

An important issue affecting genome-wide association studies with deep phenotyping (multiple correlated phenotypes) is determining the suitable family-wise significance threshold. Straightforward family-wise correction (Bonferroni) of p < 0.05 for 4.3 million genotypes and 335 phenotypes would give a threshold of p < 3.46E-11. This would be too conservative because it assumes all tests are independent. The effective number of tests, both phenotypic and genotypic, must be adjusted for the correlations between them. Spectral decomposition of the phenotype matrix and LD-based correction of the number of tested SNPs are currently used to determine an effective number of tests. In this paper, we compare these calculated estimates with permutation-determined family-wise significance thresholds. Permutations are performed by shuffling individual IDs of the genotype vector for this dataset, to preserve correlation of phenotypes. Our results demonstrate that the permutation threshold is influenced by minor allele frequency (MAF) of the SNPs, and by the number of individuals tested. For the more common SNPs (MAF > 0.1), the permutation family-wise threshold was in close agreement with spectral decomposition methods. However, for less common SNPs (0.05 < MAF ≤ 0.1), the permutation threshold calculated over all SNPs was off by orders of magnitude. This applies to the number of individuals studied (here 777) but not to very much larger numbers. Based on these findings, we propose that the threshold to find a particular level of family-wise significance may need to be established using separate permutations of the actual data for several MAF bins.

Multiple functional variants in the IL1RL1 region are pretransplant markers for risk of GVHD and infection deaths

Graft-versus-host disease (GVHD) and infections are the 2 main causes of death without relapse after allogeneic hematopoietic cell transplantation (HCT). Elevated soluble serum simulation-2 (sST2), the product of IL1RL1 in plasma/serum post-HCT, is a validated GVHD biomarker. Hundreds of SNPs at 2q12.1 have been shown to be strongly associated with sST2 concentrations in healthy populations. We therefore hypothesized that the donor genetic variants in IL1RL1 correlate with sST2 protein levels associated with patient survival outcomes after HCT. We used DISCOVeRY-BMT (Determining the Influence of Susceptibility Conveying Variants Related to 1-Year Mortality after Blood and Marrow Transplantation), a genomic study of >3000 donor-recipient pairs, to inform our hypothesis. We first measured pre-HCT plasma/serum sST2 levels in a subset of DISCOVeRY-BMT donors (n = 757) and tested the association of donor sST2 levels with donor single nucleotide polymorphisms (SNPs) in the 2q12.1 region. Donor SNPs associated with sST2 levels were then tested for association with recipient death caused by acute GVHD (aGVHD)-, infection-, and transplant-related mortality in cohorts 1 and 2. Meta-analyses of cohorts 1 and 2 were performed using fixed-effects inverse variance weighting, and P values were corrected for multiple comparisons. Donor risk alleles in rs22441131 (P _meta = .00026) and rs2310241 (P _meta = .00033) increased the cumulative incidence of aGVHD death up to fourfold and were associated with high sST2 levels. Donor risk alleles at rs4851601 (P _meta = 9.7 × 10^-7), rs13019803 (P _meta = 8.9 × 10^-6), and rs13015714 (P _meta = 5.3 × 10^-4) increased cumulative incidence of infection death to almost sevenfold and were associated with low sST2 levels. These functional variants are biomarkers of infection or aGVHD death and could facilitate donor selection, prophylaxis, and a conditioning regimen to reduce post-HCT mortality.

Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P < 5.0 × 10-8), 15 of which showed evidence for associations with at least one tumor feature (false discovery rate < 0.05). Five loci showed associations (P < 0.05) in opposite directions between luminal and non-luminal subtypes. In silico analyses showed that these five loci contained cell-specific enhancers that differed between normal luminal and basal mammary cells. The genetic correlations between five intrinsic-like subtypes ranged from 0.35 to 0.80. The proportion of genome-wide chip heritability explained by all known susceptibility loci was 54.2% for luminal A-like disease and 37.6% for triple-negative disease. The odds ratios of polygenic risk scores, which included 330 variants, for the highest 1% of quantiles compared with middle quantiles were 5.63 and 3.02 for luminal A-like and triple-negative disease, respectively. These findings provide an improved understanding of genetic predisposition to breast cancer subtypes and will inform the development of subtype-specific polygenic risk scores.

Association between CUBN gene variants, type 2 diabetes and vitamin D concentrations in an elderly Greek population

Accumulating evidence suggests a potential implication of vitamin D biological network in the pathogenesis of diabetes mellitus. The megalin-cubilin endocytotic system constitutes a key transport structure, with a modulating role in vitamin D metabolism. We aimed to assess the contribution of variants in the CUBN gene to the genetic risk of Type 2 Diabetes Mellitus (T2DM). 95 polymorphisms within CUBN were genotyped in 716 patients with T2DM and 542 controls of Greek origin. Samples were analyzed on Illumina Human PsychArray. Permutation test analysis was implemented to determine statistical significance. Twenty-five-hydroxy-vitamin-D [25(OH)D)] levels were measured in a sub-group of participants (n = 276). Permutation analysis associated rs11254375_G/T (p_emp = 0.00049, OR = 1.482), rs6602175_G/T (p_emp = 0.016, OR = 0.822), rs1801224_G/T (p_emp = 0.025, OR = 0.830), rs4366393_A/G (p_emp = 0.028, OR = 0.829) and rs7071576_A/G (p_emp = 0.04, OR = 1.219) with T2DM. Mean 25(OH)D concentrations were significantly lower in patients with T2DM compared to controls (16.70 ± 6.69 ng/ml vs 18.51 ± 6.71 ng/ml, p < 0.001), although both groups were vitamin D deficient. In a further quantitative analysis, rs41301097 was strongly associated with higher 25(OH)D concentrations (p = 5.233e-6, beta = 15.95). Our results indicate a potential role of CUBN gene in T2DM genetic susceptibility in the Greek population. These findings may also denote an indirect effect of vitamin D metabolism dysregulation on the pathogenesis of T2DM. Further studies are required to replicate our findings and clarify the complex underlying mechanisms.

Correction for multiple testing in candidate-gene methylation studies

Aim: We compared the performance of multiple testing corrections for candidate gene methylation studies, namely Sidak (accurate Bonferroni), false-discovery rate and three adjustments that incorporate the correlation between CpGs: extreme tail theory (ETT), Gao et al. (GEA), and Li and Ji methods. Materials & methods: The experiment-wide type 1 error rate was examined in simulations based on Illumina EPIC and 450K data. Results: For high-correlation genes, Sidak and false-discovery rate corrections were conservative while the Li and Ji method was liberal. The GEA method tended to be conservative unless a threshold parameter was adjusted. The ETT yielded an appropriate type 1 error rate. Conclusion: For genes with substantial correlation across measured CpGs, GEA and ETT can appropriately correct for multiple testing in candidate gene methylation studies.

Functional annotation and Bayesian fine-mapping reveals candidate genes for important agronomic traits in Holstein bulls

A hundred years of data collection in dairy cattle can facilitate powerful studies of complex traits. Cattle GWAS have identified many associated genomic regions. With increasing numbers of cattle sequenced, fine-mapping of causal variants is becoming possible. Here we imputed selected sequence variants to 27,214 Holstein bulls that have highly reliable phenotypes for 35 production, reproduction, and body conformation traits. We performed single-marker scans for the 35 traits and multi-trait tests of the three trait groups, revealing 282 candidate QTL for fine-mapping. We developed a Bayesian Fine-MAPping approach (BFMAP) to integrate fine-mapping with functional enrichment analysis. Our fine-mapping identified 69 promising candidate genes, including ABCC9, VPS13B, MGST1, SCD, MKL1, CSN1S1 for production, CHEK2, GC, KALRN for reproduction, and TMTC2, ARRDC3, ZNF613, CCND2, FGF6 for conformation traits. Collectively, these results demonstrated the utility of BFMAP, identified candidate genes, and enhanced our understanding of the genetic basis of cattle complex traits.

Genetic Predisposition to Symptomatic Lumbar Disk Herniation in Pediatric and Young Adult Patients

STUDY DESIGN

Case-control whole-genome sequencing analysis of a highly select, young cohort with symptomatic lumbar disk herniation (LDH) compared with the standard variation in a large reference population.

OBJECTIVE

To assess genetic influences predisposing pediatric and young adult patients to symptomatic LDH.

SUMMARY OF BACKGROUND DATA

LDH has traditionally been attributed to natural weakening or mechanical insult, but recent literature supports a potential genetic influence.

METHODS

Young patients with symptomatic, clinically confirmed LDH who underwent surgical treatment were included. Patients were younger than the average age of presentation, limiting the influence of environmental risks. DNA collected from these patients was compared with a reference genome (1000 Genomes Project). A genome-wide association study using whole-genome sequencing was used to characterize genetic mutations potentially associated with LDH.

RESULTS

Among the 61 candidate genes flagged, 20 had missense mutations in 2 or more LDH cases. Missense mutations in collagen-encoding genes were observed in 12 of 15 patients (80%). A potential association with clinical presentation was indicated by odds ratios of key single-nucleotide polymorphism (SNP) variants in genes that encode collagen. Relative to the reference population, the LDH cohort demonstrated two statistically significant SNP variants in the gene encoding for aggrecan, a protein that facilitates load-bearing properties in the cartilaginous end plate. Aggrecan genes SNPs rs3817428 and rs11638262 were significantly associated with decreased odds of symptomatic LDH: odds ratio 0.05 (0.02-0.11) and 0.04 (0-0.26), respectively (P < 1 × 10 for both).

CONCLUSION

These results suggest that collagen-encoding variants may be a genetic risk factor for LDH. They also shed new light on the role of variants that impact aggrecan, which sustains the cartilaginous end plate. Genetic predisposition to LDH may therefore be related to a multimodal combination of mutations that affect the nucleus pulposus, annulus fibrosus, and the cartilaginous end plates.

LEVEL OF EVIDENCE

4.

HisCoM-GGI: Hierarchical structural component analysis of gene-gene interactions

Although genome-wide association studies (GWAS) have successfully identified thousands of single nucleotide polymorphisms (SNPs) associated with common diseases, these observations are limited for fully explaining "missing heritability". Determining gene-gene interactions (GGI) are one possible avenue for addressing the missing heritability problem. While many statistical approaches have been proposed to detect GGI, most of these focus primarily on SNP-to-SNP interactions. While there are many advantages of gene-based GGI analyses, such as reducing the burden of multiple-testing correction, and increasing power by aggregating multiple causal signals across SNPs in specific genes, only a few methods are available. In this study, we proposed a new statistical approach for gene-based GGI analysis, "Hierarchical structural CoMponent analysis of Gene-Gene Interactions" (HisCoM-GGI). HisCoM-GGI is based on generalized structured component analysis, and can consider hierarchical structural relationships between genes and SNPs. For a pair of genes, HisCoM-GGI first effectively summarizes all possible pairwise SNP-SNP interactions into a latent variable, from which it then performs GGI analysis. HisCoM-GGI can evaluate both gene-level and SNP-level interactions. Through simulation studies, HisCoM-GGI demonstrated higher statistical power than existing gene-based GGI methods, in analyzing a GWAS of a Korean population for identifying GGI associated with body mass index. Resultantly, HisCoM-GGI successfully identified 14 potential GGI, two of which, (NCOR2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo></mml:math> SPOCK1) and (LINGO2 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mo>×</mml:mo></mml:math> ZNF385D) were successfully replicated in independent datasets. We conclude that HisCoM-GGI method may be a valuable tool for genome to identify GGI in missing heritability, allowing us to better understand the biological genetic mechanisms of complex traits. We conclude that HisCoM-GGI method may be a valuable tool for genome to identify GGI in missing heritability, allowing us to better understand biological genetic mechanisms of complex traits. An implementation of HisCoM-GGI can be downloaded from the website ( http://statgen.snu.ac.kr/software/hiscom-ggi ).

Machine learning identifies interacting genetic variants contributing to breast cancer risk: A case study in Finnish cases and controls

We propose an effective machine learning approach to identify group of interacting single nucleotide polymorphisms (SNPs), which contribute most to the breast cancer (BC) risk by assuming dependencies among BCAC iCOGS SNPs. We adopt a gradient tree boosting method followed by an adaptive iterative SNP search to capture complex non-linear SNP-SNP interactions and consequently, obtain group of interacting SNPs with high BC risk-predictive potential. We also propose a support vector machine formed by the identified SNPs to classify BC cases and controls. Our approach achieves mean average precision (mAP) of 72.66, 67.24 and 69.25 in discriminating BC cases and controls in KBCP, OBCS and merged KBCP-OBCS sample sets, respectively. These results are better than the mAP of 70.08, 63.61 and 66.41 obtained by using a polygenic risk score model derived from 51 known BC-associated SNPs, respectively, in KBCP, OBCS and merged KBCP-OBCS sample sets. BC subtype analysis further reveals that the 200 identified KBCP SNPs from the proposed method performs favorably in classifying estrogen receptor positive (ER+) and negative (ER-) BC cases both in KBCP and OBCS data. Further, a biological analysis of the identified SNPs reveals genes related to important BC-related mechanisms, estrogen metabolism and apoptosis.

Exome chip analyses identify genes affecting mortality after HLA-matched unrelated-donor blood and marrow transplantation

Although survival outcomes have significantly improved, up to 40% of patients die within 1 year of HLA-matched unrelated-donor blood and marrow transplantation (BMT). To identify non-HLA genetic contributors to mortality after BMT, we performed the first exome-wide association study in the DISCOVeRY-BMT cohorts using the Illumina HumanExome BeadChip. This study includes 2473 patients with acute myeloid leukemia, acute lymphoblastic leukemia, or myelodysplastic syndrome and 2221 10/10 HLA-matched donors treated from 2000 to 2011. Single-variant and gene-level analyses were performed on overall survival (OS), transplantation-related mortality (TRM), and disease-related mortality (DRM). Genotype mismatches between recipients and donors in a rare nonsynonymous variant of testis-expressed gene TEX38 significantly increased risk of TRM, which was more dramatic when either the recipient or donor was female. Using the SKAT-O test to evaluate gene-level effects, variant genotypes of OR51D1 in recipients were significantly associated with OS and TRM. In donors, 4 (ALPP, EMID1, SLC44A5, LRP1), 1 (HHAT), and 2 genes (LYZL4, NT5E) were significantly associated with OS, TRM, and DRM, respectively. Inspection of NT5E crystal structures showed 4 of the associated variants affected the enzyme structure and likely decreased the catalytic efficiency of the enzyme. Further confirmation of these findings and additional functional studies may provide individualized risk prediction and prognosis, as well as alternative donor selection strategies.

Investigation of single and synergic effects of NLRC5 and PD-L1 variants on the risk of colorectal cancer

Constitutive activation of interferon signaling pathways has been reported in colorectal cancer (CRC), leading to a strong CD8+ T cell response through stimulation of NLRC5 expression. Primed CD8+ T cell expansion, however, may be negatively regulated by PD-L1 expression. Additionally, aberrant PD-L1 expression enables cancer cells to escape the immune attack. Our study aimed to select potential regulatory variants in the NLRC5 and PD-L1 genes by using several online in silico tools, such as UCSC browser, HaploReg, Regulome DB, Gtex Portal, microRNA and transcription factor binding site prediction tools and to investigate their influence on CRC risk in a Czech cohort of 1424 CRC patients and 1114 healthy controls. Logistic regression analysis adjusted for age and gender reported a moderate association between rectal cancer risk and two NLRC5 SNPs, rs1684575 T>G (OR: 1.60, 95% CI: 1.13-2.27, recessive model) and rs3751710 (OR: 0.70, 95% CI: 0.51-0.96, dominant model). Given that a combination of genetic variants, rather than a single polymorphism, may explain better the genetic etiology of CRC, we studied the interplay between the variants within NLRC5, PD-L1 and the previously genotyped IFNGR1 and IFNGR2 variants, to evaluate their involvement in the risk of CRC development. Overall we obtained 18 pair-wise interactions within and between the NLRC5 ad PD-L1 genes and 6 more when IFNGR variants were added. Thirteen out of the 24 interactions were below the threshold for the FDR calculated and controlled at an arbitrary level q*<0.10. Furthermore, the interaction IFNGR2 rs1059293 C>T-NLRC5 rs289747 G>A (P<0.0001) remained statistically significant even after Bonferroni correction. Our data suggest that not only a single genetic variant but also an interaction between two or more variants within genes involved in immune regulation may play important roles in the onset of CRC, providing therefore novel biological information, which could eventually improve CRC risk management but also PD-1-based immunotherapy in CRC.

A Genome-Wide Search for Bipolar Disorder Risk Loci Modified by Mitochondrial Genome Variation

Mitochondrial DNA mutations have been reported to be associated with bipolar disorder (BD). In this study, we performed genome-wide analyses to assess mitochondrial single-nucleotide polymorphism (mtSNP) effects on BD risk and early-onset BD (EOBD) among BD patients, focusing on interaction effects between nuclear SNPs (nSNPs) and mtSNPs. Common nSNP and mtSNP data from European American BD cases (n = 1,001) and controls (n = 1,034) from the Genetic Association Information Network BD study were analyzed to assess the joint effect of nSNP and nSNP-mtSNP interaction on the risk of BD and EOBD. The effect of nSNP-mtSNP interactions was also assessed. For BD risk, the strongest evidence of an association was obtained for nSNP rs1880924 in MGAM and mtSNP rs3088309 in CytB (p_joint = 8.2 × 10^-8, p_int = 1.4 × 10^-4). Our results also suggest that the minor allele of the nSNP rs583990 in CTNNA2 increases the risk of EOBD among carriers of the mtSNP rs3088309 minor allele, while the nSNP has no effect among those carrying the mtSNP major allele (OR = 4.53 vs. 1.05, p_joint = 2.1 × 10^-7, p_int = 1.16 × 10^-6). While our results are not statistically significant after multiple testing correction and a large-sample replication is required, our exploratory study demonstrates the potential importance of considering the mitochondrial genome for identifying genetic factors associated with BD.

Variants in the fetal genome near FLT1 are associated with risk of preeclampsia

Preeclampsia, which affects approximately 5% of pregnancies, is a leading cause of maternal and perinatal death. The causes of preeclampsia remain unclear, but there is evidence for inherited susceptibility. Genome-wide association studies (GWAS) have not identified maternal sequence variants of genome-wide significance that replicate in independent data sets. We report the first GWAS of offspring from preeclamptic pregnancies and discovery of the first genome-wide significant susceptibility locus (rs4769613; P = 5.4 × 10^-11) in 4,380 cases and 310,238 controls. This locus is near the FLT1 gene encoding Fms-like tyrosine kinase 1, providing biological support, as a placental isoform of this protein (sFlt-1) is implicated in the pathology of preeclampsia. The association was strongest in offspring from pregnancies in which preeclampsia developed during late gestation and offspring birth weights exceeded the tenth centile. An additional nearby variant, rs12050029, associated with preeclampsia independently of rs4769613. The newly discovered locus may enhance understanding of the pathophysiology of preeclampsia and its subtypes.

A systematic review on the association between inflammatory genes and cognitive decline in non-demented elderly individuals

Cognitive impairment, or decline, is not only a feature of Alzheimer׳s disease and other forms of dementia but also normal ageing. Abundant evidence from epidemiological studies points towards perturbed inflammatory mechanisms in aged individuals, though the cause-effect nature of this apparent relationship is difficult to establish. Genetic association studies focusing on polymorphism in and around inflammatory genes represent a viable approach to establish whether inflammatory mechanisms might play a causal role in cognitive decline, whilst also enabling the identification of specific genes potentially influencing specific cognitive facets. Thus, here we provide a review of published genetic association studies investigating inflammatory genes in the context of cognitive decline in elderly, non-demented, samples. Numerous candidate gene association studies have been performed to date, focusing almost exclusively on genes encoding major cytokines. Some of these studies report significant cognitive domain-specific associations implicating Interleukin 1β (IL1β) (rs16944), Tumour Necrosis Factor α (TNFα) (rs1800629) and C-reactive protein (CRP) in various domains of cognitive function. However, the majority of these studies are lacking in statistical power and have other methodological limitations, suggesting some of them may have yielded false positive results. Genome-wide association studies have implicated less direct and less obvious regulators of inflammatory processes (i.e., PDE7A, HS3ST4, SPOCK3), indicating that a shift away from the major cytokine-encoding genes in future studies will be important. Furthermore, better cohesion across studies with regards to the cognitive test batteries administered to participants along with the continued application of longitudinal designs will be vital.

gsSKAT: Rapid gene set analysis and multiple testing correction for rare-variant association studies using weighted linear kernels

Next-generation sequencing technologies have afforded unprecedented characterization of low-frequency and rare genetic variation. Due to low power for single-variant testing, aggregative methods are commonly used to combine observed rare variation within a single gene. Causal variation may also aggregate across multiple genes within relevant biomolecular pathways. Kernel-machine regression and adaptive testing methods for aggregative rare-variant association testing have been demonstrated to be powerful approaches for pathway-level analysis, although these methods tend to be computationally intensive at high-variant dimensionality and require access to complete data. An additional analytical issue in scans of large pathway definition sets is multiple testing correction. Gene set definitions may exhibit substantial genic overlap, and the impact of the resultant correlation in test statistics on Type I error rate control for large agnostic gene set scans has not been fully explored. Herein, we first outline a statistical strategy for aggregative rare-variant analysis using component gene-level linear kernel score test summary statistics as well as derive simple estimators of the effective number of tests for family-wise error rate control. We then conduct extensive simulation studies to characterize the behavior of our approach relative to direct application of kernel and adaptive methods under a variety of conditions. We also apply our method to two case-control studies, respectively, evaluating rare variation in hereditary prostate cancer and schizophrenia. Finally, we provide open-source R code for public use to facilitate easy application of our methods to existing rare-variant analysis results.

Assessment of variation in immunosuppressive pathway genes reveals TGFBR2 to be associated with risk of clear cell ovarian cancer

BACKGROUND

Regulatory T (Treg) cells, a subset of CD4+ T lymphocytes, are mediators of immunosuppression in cancer, and, thus, variants in genes encoding Treg cell immune molecules could be associated with ovarian cancer.

METHODS

In a population of 15,596 epithelial ovarian cancer (EOC) cases and 23,236 controls, we measured genetic associations of 1,351 SNPs in Treg cell pathway genes with odds of ovarian cancer and tested pathway and gene-level associations, overall and by histotype, for the 25 genes, using the admixture likelihood (AML) method. The most significant single SNP associations were tested for correlation with expression levels in 44 ovarian cancer patients.

RESULTS

The most significant global associations for all genes in the pathway were seen in endometrioid ( p = 0.082) and clear cell ( p = 0.083), with the most significant gene level association seen with TGFBR2 ( p = 0.001) and clear cell EOC. Gene associations with histotypes at p < 0.05 included: IL12 ( p = 0.005 and p = 0.008, serous and high-grade serous, respectively), IL8RA ( p = 0.035, endometrioid and mucinous), LGALS1 ( p = 0.03, mucinous), STAT5B ( p = 0.022, clear cell), TGFBR1 ( p = 0.021 endometrioid) and TGFBR2 ( p = 0.017 and p = 0.025, endometrioid and mucinous, respectively).

CONCLUSIONS

Common inherited gene variation in Treg cell pathways shows some evidence of germline genetic contribution to odds of EOC that varies by histologic subtype and may be associated with mRNA expression of immune-complex receptor in EOC patients.

A Large Genome-Wide Association Study of Age-Related Hearing Impairment Using Electronic Health Records

Age-related hearing impairment (ARHI), one of the most common sensory disorders, can be mitigated, but not cured or eliminated. To identify genetic influences underlying ARHI, we conducted a genome-wide association study of ARHI in 6,527 cases and 45,882 controls among the non-Hispanic whites from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. We identified two novel genome-wide significant SNPs: rs4932196 (odds ratio = 1.185, p = 4.0x10^-11), 52Kb 3’ of ISG20, which replicated in a meta-analysis of the other GERA race/ethnicity groups (1,025 cases, 12,388 controls, p = 0.00094) and in a UK Biobank case-control analysis (30,802 self-reported cases, 78,586 controls, p = 0.015); and rs58389158 (odds ratio = 1.132, p = 1.8x10^-9), which replicated in the UK Biobank (p = 0.00021). The latter SNP lies just outside exon 8 and is highly correlated (r² = 0.96) with the missense SNP rs5756795 in exon 7 of TRIOBP, a gene previously associated with prelingual nonsyndromic hearing loss. We further tested these SNPs in phenotypes from audiologist notes available on a subset of GERA (4,903 individuals), stratified by case/control status, to construct an independent replication test, and found a significant effect of rs58389158 on speech reception threshold (SRT; overall GERA meta-analysis p = 1.9x10^-6). We also tested variants within exons of 132 other previously-identified hearing loss genes, and identified two common additional significant SNPs: rs2877561 (synonymous change in ILDR1, p = 6.2x10^-5), which replicated in the UK Biobank (p = 0.00057), and had a significant GERA SRT (p = 0.00019) and speech discrimination score (SDS; p = 0.0019); and rs9493627 (missense change in EYA4, p = 0.00011) which replicated in the UK Biobank (p = 0.0095), other GERA groups (p = 0.0080), and had a consistent significant result for SRT (p = 0.041) and suggestive result for SDS (p = 0.081). Large cohorts with GWAS data and electronic health records may be a useful method to characterize the genetic architecture of ARHI.

Age-related hearing impairment (ARHI) is one of the most common sensory disorders. While ARHI effects can be mitigated with current technologies, it cannot be cured or eliminated. It is thus hoped that identification of genetic influences on ARHI may one day lead to curative therapies. Towards this goal, the current study utilized electronic health record data from non-Hispanic whites in the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort to conduct a genome-wide association study of ARHI, and tested the significant variants for replication in other GERA race/ethnicity groups, independent GERA phenotypes, and self-reported ARHI from the UK Biobank. We discovered two genome-wide significant SNPs. The first was novel and near ISG20. The second was in TRIOBP, a gene previously associated with prelingual nonsyndromic hearing loss. Motivated by our TRIOBP results, we also looked at exons in known hearing loss genes, and identified two additional SNPs, rs2877561 in ILDR1 and rs9493672 in EYA4 (at a significance threshold adjusted for number of SNPs in those regions). These results suggest that large cohorts with GWAS data and electronic health records may be a useful method to characterize the genetic architecture of ARHI.

LandScape: a simple method to aggregate p-values and other stochastic variables without a priori grouping

In many areas of science it is custom to perform many, potentially millions, of tests simultaneously. To gain statistical power it is common to group tests based on a priori criteria such as predefined regions or by sliding windows. However, it is not straightforward to choose grouping criteria and the results might depend on the chosen criteria. Methods that summarize, or aggregate, test statistics or p-values, without relying on a priori criteria, are therefore desirable. We present a simple method to aggregate a sequence of stochastic variables, such as test statistics or p-values, into fewer variables without assuming a priori defined groups. We provide different ways to evaluate the significance of the aggregated variables based on theoretical considerations and resampling techniques, and show that under certain assumptions the FWER is controlled in the strong sense. Validity of the method was demonstrated using simulations and real data analyses. Our method may be a useful supplement to standard procedures relying on evaluation of test statistics individually. Moreover, by being agnostic and not relying on predefined selected regions, it might be a practical alternative to conventionally used methods of aggregation of p-values over regions. The method is implemented in Python and freely available online (through GitHub, see the Supplementary information).

Genome-wide time-to-event analysis on smoking progression stages in a family-based study

BACKGROUND

Various pivotal stages in smoking behavior can be identified, including initiation, conversion from experimenting to established use, development of tolerance, and cessation. Previous studies have shown high heritability for age of smoking initiation and cessation; however, time-to-event genome-wide association studies aiming to identify underpinning genes that accelerate or delay these transitions are missing to date.

METHODS

We investigated which single nucleotide polymorphisms (SNPs) across the whole genome contribute to the hazard ratio of transition between different stages of smoking behavior by performing time-to-event analyses within a large Finnish twin family cohort (N = 1962), and further conducted mediation analyses of plausible intermediate traits for significant SNPs.

RESULTS

Genome-wide significant signals were detected for three of the four transitions: (1) for smoking cessation on 10p14 (P = 4.47e-08 for rs72779075 flanked by RP11-575N15 and GATA3), (2) for tolerance on 11p13 (P = 1.29e-08 for rs11031684 in RP1-65P5.1), mediated by smoking quantity, and on 9q34.12 (P = 3.81e-08 for rs2304808 in FUBP3), independent of smoking quantity, and (3) for smoking initiation on 19q13.33 (P = 3.37e-08 for rs73050610 flanked by TRPM4 and SLC6A16) in analysis adjusted for first time sensations. Although our top SNPs did not replicate, another SNP in the TRPM4-SLC6A16 gene region showed statistically significant association after region-based multiple testing correction in an independent Australian twin family sample.

CONCLUSION

Our results suggest that the functional effect of the TRPM4-SLC6A16 gene region deserves further investigation, and that complex neurotransmitter networks including dopamine and glutamate may play a critical role in smoking initiation. Moreover, comparison of these results implies that genetic contributions to the complex smoking behavioral phenotypes vary among the transitions.

Association Analysis Suggests SOD2 as a Newly Identified Candidate Gene Associated With Leprosy Susceptibility

Genetic studies have identified several genes and genomic regions contributing to the control of host susceptibility to leprosy. Here, we test variants of the positional and functional candidate gene SOD2 for association with leprosy in 2 independent population samples. Family-based analysis revealed an association between leprosy and allele G of marker rs295340 (P = .042) and borderline evidence of an association between leprosy and alleles C and A of markers rs4880 (P = .077) and rs5746136 (P = .071), respectively. Findings were validated in an independent case-control sample for markers rs295340 (P = .049) and rs4880 (P = .038). These results suggest SOD2 as a newly identified gene conferring susceptibility to leprosy.

Synaptotagmin XI in Parkinson's disease: New evidence from an association study in Spain and Mexico

INTRODUCTION

The pathophysiology of PD (Parkinson's disease) has been related to the ubiquitin proteasome system and oxidative stress. Parkin acts as ubiquitin ligase on several substrates. Because genetic variants often have different frequencies across populations, population specific analyses are necessary to complement and validate results from genome-wide association studies.

METHODS

We carried out an association study with genes coding for parkin substrates and cellular stress components in the Galician population (Northern Spain). SNCA and MAPT SNPs were also analyzed. We studied 75 SNPs in a discovery sample of 268 PD patients and 265 controls from Galicia. A replication sample of 271 patients and 260 controls was recruited from Mexico City.

RESULTS

We observed significant association between PD and SNPs in MAPT. Nominal p-values<0.05 were obtained in the Galician cohort for SNPs in SYT11, coding for synaptotagmin XI. These results were replicated in the Mexican sample.

DISCUSSION

The associated markers lie within a ~140kb strong linkage disequilibrium segment that harbors several candidate genes, including SYT11. SNPs from the GBA-SYT11-RAB25 region have been previously associated with PD, however the functionally relevant variants remain unknown. Our data support a likely role of genetic factors within 1q22 in PD susceptibility.

AGGrEGATOr: A Gene-based GEne-Gene interActTiOn test for case-control association studies

Among the large of number of statistical methods that have been proposed to identify gene-gene interactions in case-control genome-wide association studies (GWAS), gene-based methods have recently grown in popularity as they confer advantage in both statistical power and biological interpretation. All of the gene-based methods jointly model the distribution of single nucleotide polymorphisms (SNPs) sets prior to the statistical test, leading to a limited power to detect sums of SNP-SNP signals. In this paper, we instead propose a gene-based method that first performs SNP-SNP interaction tests before aggregating the obtained

A New Correction for Multiple Testing in Gene-Gene Interaction Studies

A major problem in gene-gene interaction studies in large marker panels is how to correct for multiple testing while accounting for the dependence between marker pairs due to the presence of linkage disequilibrium. The "gold standard" approach is to perform permutations of case/control labels. However, this is often not feasible in practice, due to computational demands. Here, we propose a correction based on the effective number of independent tests of interaction between marker pairs. This number depends on the effective number of independent single-marker tests. We tested its validity using simulated samples, as well as that of another correction of marker pair tests. We showed that our approach was valid while the other correction strongly underestimated the effective number of independent tests. Our method provides estimates of the effective number of independent tests close to those reported in the literature for a Genome-Wide Interaction Study on a 550K chip. Our correction method is quick and simple, and can be applied whatever the marker panel and the underlying linkage disequilibrium pattern.

Genomewide association study of reproductive efficiency in female cattle

Reproductive efficiency is of economic importance in commercial beef cattle production, as failure to achieve pregnancy reduces the number of calves marketed per cow exposed. Identification of genetic markers with predictive merit for reproductive success would facilitate early selection of sires with daughters having improved reproductive rate without increasing generation intervals. To identify regions of the genome harboring variation affecting reproductive success, we applied a genomewide association study (GWAS) approach based on the >700,000 SNP marker assay, using a procedure based on genotyping multianimal pools of DNA to increase the number of animals that could be genotyped with available resources. Cows from several populations were classified according to reproductive efficiency, and DNA was pooled within population and phenotype prior to genotyping. Populations evaluated included a research population at the U.S. Meat Animal Research Center, 2 large commercial ranch populations, and a number of smaller populations (<100 head) across the United States. We detected 2 SNP with significant genomewide association (P ≤ 1.49 × 10(-7)), on BTA21 and BTA29, 3 SNP with suggestive associations (P ≤ 2.91 × 10(-6)) on BTA5, and 1 SNP with suggestive association each on BTA1 and BTA25. In addition to our novel findings, we confirmed previously published associations for SNP on BTA-X and all autosomes except 3 (BTA21, BTA22, and BTA28) encompassing substantial breed diversity including Bos indicus and Bos taurus breeds. The study identified regions of the genome associated with reproductive efficiency, which are being targeted for further analysis to develop robust marker systems, and demonstrated that DNA pooling can be used to substantially reduce the cost of GWAS in cattle.