On the Usage of HWE for Identifying Genotyping Errors

Comparative Analysis of Runs of Homozygosity Islands in Indigenous and Commercial Chickens Revealed Candidate Loci for Disease Resistance and Production Traits

Runs of homozygosity (ROH) are contiguous stretches of identical genomic regions inherited from both parents. Assessment of ROH in livestock species contributes significantly to our understanding of genetic health, population genetic structure, selective pressure and conservation efforts. In this study, whole genome re-sequencing data from 140 birds of 10 Iranian indigenous chicken ecotypes, 3 commercial chicken breeds and 1 red junglefowl (RJF) population were used to investigate their population genetic structure, ROH characteristics (length and frequency) and genomic inbreeding coefficients (FROH). Additionally, we examined ROH islands for selection footprints in the indigenous chicken populations. Our results revealed distinct genetic backgrounds, among which the White Leghorn breed exhibited the greatest genetic distance from other populations, while the gamecock populations formed a separate cluster. We observed significant differences in ROH characteristics, in which the commercial breeds showed a higher number of ROH compared to indigenous chickens and red junglefowls. Short ROH ranging from 0.1 to 1 Mb were dominant among the populations. The Arian line had the highest mean length of ROH, while the White Leghorn breed showed the highest number of ROH. Among indigenous chickens, the Lari-Afghani ecotype exhibited the highest FROH, but the Sari inherited the richest genetic diversity. Interestingly, GGA16 carried no ROH in the red junglefowls, whereas GGA22 had the highest FROH across all populations, except in the Isfahan ecotype. We also identified ROH islands associated with genetic adaptations in indigenous ecotypes. These islands harboured immune-related genes contributing to disease resistance (TLR2, TICAM1, IL22RA1, NOS2, CCL20 and IFNLR1), heat tolerance and oxidative stress response (NFKB1, HSF4, OSGIN1 and BDNF), and muscle development, lipid metabolism and reproduction (MEOX2, CEBPB, CDS2 and GnRH-I). Overall, this study highlights the genetic potential of indigenous chickens to survive and adapt to their respective environments.

Genome-wide study of linkage disequilibrium, population structure, and inbreeding in Iranian indigenous sheep breeds

Knowledge of linkage disequilibrium (LD), genetic structure and genetic diversity are some key parameters to study the breeding history of indigenous small ruminants. In this study, the OvineSNP50 Bead Chip array was used to estimate and compare LD, genetic diversity, effective population size (Ne) and genomic inbreeding in 186 individuals, from three Iranian indigenous sheep breeds consisting of Baluchi (n = 96), Lori-Bakhtiari (n = 47) and Zel (n = 47). The results of principal component analysis (PCA) revealed that all animals were allocated to the groups that they sampled and the admixture analysis revealed that the structure within the populations is best explained when separated into three groups (K  =  3). The average r2 values estimated between adjacent single nucleotide polymorphisms (SNPs) at distances up to 10Kb, were 0.388±0.324, 0.353±0.311, and 0.333±0.309 for Baluchi, Lori-Bakhtiari and Zel, respectively. Estimation of genetic diversity and effective population size (Ne) showed that the Zel breed had the highest heterozygosity and Ne, whereas the lowest value was found in Baluchi breed. Estimation of genomic inbreeding using FROH (based on the long stretches of consecutive homozygous genotypes) showed the highest inbreeding coefficient in Baluchi and the lowest in Zel breed that could be due to higher pressure of artificial selection on Baluchi breed. The results of genomic inbreeding and Ne showed an increase in sharing haplotypes in Baluchi, leading to the enlargement of LD and the consequences of linkage disequilibrium and haplotype blocks confirmed this point. Also, the persistence of the LD phase between Zel and Lori-Bakhtiari was highest indicating that these two breeds would be combined in a multi-breed training population in genomic selection studies.

Explore the role of CR1 genetic variants in late-onset Alzheimer's disease susceptibility

BACKGROUND

Complement component (3b/4b) receptor 1 (CR1) is an interesting candidate gene which has a close connection with Alzheimer's disease, and its polymorphisms have been reported to link to the late-onset Alzheimer's disease (LOAD) susceptibility. However, the findings of these related studies are inconsistent. Objective To explore the effect of CR1 genetic variants in LOAD susceptibility. MethodsWe searched relevant studies for the period up to 1 November 2020. And odds ratios (ORs) and their 95% confidence intervals (CIs) were utilized to assess the strength of the association. In addition, we carried out a case-control association study to assess their genetic association.

RESULTS

Finally, a total of 30 articles with 30108 LOAD cases and 37895 controls were included. Significant allele frequency between LOAD patients and controls was observed in rs3818361 and rs6656401 (rs3818361, T vs. C: OR,1.18; 95% CI, 1.13-1.23; rs6656401, A vs. G: OR, 1.23; 95% CI, 1.10-1.36). Moreover, these results remain significant in subgroup of rs3818361 in Asia or America (OR,1.26; 95% CI,1.06-1.45; OR, 1.18; 95% CI, 1.13-1.24, respectively) and rs6656401 in Europe (OR = 1.26; 95% CI, 1.09-1.42). In addition, the two single nucleotide polymorphisms were proved to significantly increase LOAD risk in the overall population under the dominant model (OR = 1.12; 95% CI, 1.02-1.21; OR = 1.18, 95% CI, 1.15-1.22, respectively). Our case-control study showed that the distribution of rs6656401 genotype was significant (P = 0.000; OR, 6.889; 95% CI, 2.709-17.520), suggesting the A allele of rs6656401 is the risk allele.

CONCLUSION

These available data indicate that rs6656401 in CR1 is significant to increase LOAD risk.

A network algorithm for the X chromosomal exact test for Hardy-Weinberg equilibrium with multiple alleles

Statistical methodology for testing the Hardy–Weinberg equilibrium at X chromosomal variants has recently experienced considerable development. Up to a few years ago, testing X chromosomal variants for equilibrium was basically done by applying autosomal test procedures to females only. At present, male alleles can be taken into account in asymptotic and exact test procedures for both the bi‐ and multiallelic case. However, current X chromosomal exact procedures for multiple alleles rely on a classical full enumeration algorithm and are computationally expensive, and in practice not feasible for more than three alleles. In this article, we extend the autosomal network algorithm for exact Hardy–Weinberg testing with multiple alleles to the X chromosome, achieving considerable reduction in computation times for multiallelic variants with up to five alleles. The performance of the X chromosomal network algorithm is assessed in a simulation study. Beyond four alleles, a permutation test is, in general, the more feasible approach. A detailed description of the algorithm is given, and examples of X chromosomal indels and microsatellites are discussed.

Population genomics of rapid evolution in natural populations: polygenic selection in response to power station thermal effluents

BACKGROUND

Examples of rapid evolution are common in nature but difficult to account for with the standard population genetic model of adaptation. Instead, selection from the standing genetic variation permits rapid adaptation via soft sweeps or polygenic adaptation. Empirical evidence of this process in nature is currently limited but accumulating.

RESULTS

We provide genome-wide analyses of rapid evolution in Fundulus heteroclitus populations subjected to recently elevated temperatures due to coastal power station thermal effluents using 5449 SNPs across two effluent-affected and four reference populations. Bayesian and multivariate analyses of population genomic structure reveal a substantial portion of genetic variation that is most parsimoniously explained by selection at the site of thermal effluents. An FST outlier approach in conjunction with additional conservative requirements identify significant allele frequency differentiation that exceeds neutral expectations among exposed and closely related reference populations. Genomic variation patterns near these candidate loci reveal that individuals living near thermal effluents have rapidly evolved from the standing genetic variation through small allele frequency changes at many loci in a pattern consistent with polygenic selection on the standing genetic variation.

CONCLUSIONS

While the ultimate trajectory of selection in these populations is unknown and we survey only a minority of genomic loci, our findings suggest that polygenic models of adaptation may play important roles in large, natural populations experiencing recent selection due to environmental changes that cause broad physiological impacts.

An exome sequencing based approach for genome-wide association studies in the dog

Genome-wide association studies (GWAS) are widely used to identify loci associated with phenotypic traits in the domestic dog that has emerged as a model for Mendelian and complex traits. However, a disadvantage of GWAS is that it always requires subsequent fine-mapping or sequencing to pinpoint causal mutations. Here, we performed whole exome sequencing (WES) and canine high-density (cHD) SNP genotyping of 28 dogs from 3 breeds to compare the SNP and linkage disequilibrium characteristics together with the power and mapping precision of exome-guided GWAS (EG-GWAS) versus cHD-based GWAS. Using simulated phenotypes, we showed that EG-GWAS has a higher power than cHD to detect associations within target regions and less power outside target regions, with power being influenced further by sample size and SNP density. We analyzed two real phenotypes (hair length and furnishing), that are fixed in certain breeds to characterize mapping precision of the known causal mutations. EG-GWAS identified the associated exonic and 3'UTR variants within the FGF5 and RSPO2 genes, respectively, with only a few samples per breed. In conclusion, we demonstrated that EG-GWAS can identify loci associated with Mendelian phenotypes both within and across breeds.

Global genetic variation of select opiate metabolism genes in self-reported healthy individuals

CYP2D6 is a key pharmacogene encoding an enzyme impacting poor, intermediate, extensive and ultrarapid phase I metabolism of many marketed drugs. The pharmacogenetics of opiate drug metabolism is particularly interesting due to the relatively high incidence of addiction and overdose. Recently, trans-acting opiate metabolism and analgesic response enzymes (UGT2B7, ABCB1, OPRM1 and COMT) have been incorporated into pharmacogenetic studies to generate more comprehensive metabolic profiles of patients. With use of massively parallel sequencing, it is possible to identify additional polymorphisms that fine tune, or redefine, previous pharmacogenetic findings, which typically rely on targeted approaches. The 1000 Genomes Project data were analyzed to describe population genetic variation and statistics for these five genes in self-reported healthy individuals in five global super- and 26 sub-populations. Findings on the variation of these genes in various populations expand baseline understanding of pharmacogenetically relevant polymorphisms for future studies of affected cohorts.

A genome-wide study of Hardy-Weinberg equilibrium with next generation sequence data

Statistical tests for Hardy–Weinberg equilibrium have been an important tool for detecting genotyping errors in the past, and remain important in the quality control of next generation sequence data. In this paper, we analyze complete chromosomes of the 1000 genomes project by using exact test procedures for autosomal and X-chromosomal variants. We find that the rate of disequilibrium largely exceeds what might be expected by chance alone for all chromosomes. Observed disequilibrium is, in about 60% of the cases, due to heterozygote excess. We suggest that most excess disequilibrium can be explained by sequencing problems, and hypothesize mechanisms that can explain exceptional heterozygosities. We report higher rates of disequilibrium for the MHC region on chromosome 6, regions flanking centromeres and p-arms of acrocentric chromosomes. We also detected long-range haplotypes and areas with incidental high disequilibrium. We report disequilibrium to be related to read depth, with variants having extreme read depths being more likely to be out of equilibrium. Disequilibrium rates were found to be 11 times higher in segmental duplications and simple tandem repeat regions. The variants with significant disequilibrium are seen to be concentrated in these areas. For next generation sequence data, Hardy–Weinberg disequilibrium seems to be a major indicator for copy number variation.

Testing Departure from Hardy-Weinberg Proportions

The Hardy-Weinberg principle, one of the most important principles in population genetics, was originally developed for the study of allele frequency changes in a population over generations. It is now, however, widely used in studies of human diseases to detect inbreeding, population stratification, and genotyping errors. For assessment of deviation from Hardy-Weinberg proportions in data, the most popular approaches include the asymptotic Pearson's chi-squared goodness-of-fit test and the exact test. Pearson's chi-squared goodness-of-fit test is simple and straightforward, but is very sensitive to a small sample size or rare allele frequency. The exact test of Hardy-Weinberg proportions is preferable in these situations. The exact test can be performed through complete enumeration of heterozygote genotypes or on the basis of the Markov chain Monte Carlo procedure. In this chapter, we describe the Hardy-Weinberg principle and the commonly used Hardy-Weinberg proportion tests and their applications, and we demonstrate how the chi-squared test and exact test of Hardy-Weinberg proportions can be performed step-by-step using the popular software programs SAS, R, and PLINK, which have been widely used in genetic association studies, along with numerical examples. We also discuss approaches for testing Hardy-Weinberg proportions in case-control study designs that are better than traditional approaches for testing Hardy-Weinberg proportions in controls only. Finally, we note that deviation from the Hardy-Weinberg proportions in affected individuals can provide evidence for an association between genetic variants and diseases.

Genetic variation in ORMDL3 gene may contribute to the risk of asthma: a meta-analysis

BACKGROUND

Since the first genome-wide association study report of an association between the ORMDL3 rs7216389 polymorphism and asthma, many studies have been carried out to establish its role in asthma susceptibility among different ethnic groups. However, results have not been consistent across all studies, compelling us to conduct the present meta-analysis.

METHODS

A literature search for eligible studies published before January 20, 2014 was conducted in the MEDLINE, EMBASE, and CNKI databases. The association was assessed using pooled crude odds ratios (ORs) with their corresponding 95% confidence intervals (CIs).

RESULTS

A total of 18 individual studies in 15 publications (total 7904 asthma patients and 10,874 healthy controls) were included in the meta-analysis. A meta-analysis of all included studies suggested that there was a highly significant risk effect conferred by the rs7216389*T allele on asthma susceptibility. In addition, we performed stratified analyses to evaluate ethnicity-specific and age-specific effects. Our subgroup analyses based on ethnicity and age-of-onset confirmed the role of the ORMDL3 rs7216389 polymorphism in conferring susceptibility to both childhood- and adult-onset asthma, especially in Caucasians and Asians.

CONCLUSIONS

The results of this meta-analysis firmly established that genetic variation at the rs7216389 locus, which controls the expression of the ORMDL3, may be a major, independent predisposing factor for asthma in ethnically diverse populations. However, further systematic studies are needed to determine the underlying mechanisms of this association.

Signatures of selection in sheep bred for resistance or susceptibility to gastrointestinal nematodes

Background

Gastrointestinal nematodes are one of the most serious causes of disease in domestic ruminants worldwide. There is considerable variation in resistance to gastrointestinal nematodes within and between sheep breeds, which appears to be due to underlying genetic diversity. Through selection of resistant animals, rapid genetic progress has been demonstrated in both research and commercial flocks. Recent advances in genome sequencing and genomic technologies provide new opportunities to understand the ovine host response to gastrointestinal nematodes at the molecular level, and to identify polymorphisms conferring nematode resistance.

Results

Divergent lines of Romney and Perendale sheep, selectively bred for high and low faecal nematode egg count, were genotyped using the Illumina® Ovine SNP50 BeadChip. The resulting genome-wide SNP data were analysed for selective sweeps on loci associated with resistance or susceptibility to gastrointestinal nematode infection. Population differentiation using F_ST and Peddrift revealed sixteen regions, which included candidate genes involved in chitinase activity and the cytokine response. Two of the sixteen regions identified were contained within previously identified QTLs associated with nematode resistance.

Conclusions

In this study we identified fourteen novel regions associated with resistance or susceptibility to gastrointestinal nematodes. Results from this study support the hypothesis that host resistance to internal nematode parasites is likely to be controlled by a number of loci of moderate to small effects.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-637) contains supplementary material, which is available to authorized users.

Promoter methylation and polymorphism of E-cadherin gene may confer a risk to prostate cancer: a meta-analysis based on 22 studies

Emerging evidence has suggested that -160C/A polymorphism and promoter methylation of E-cadherin gene may contribute to the risk of prostate cancer. However, the results are still conflicting. We aim to systematically evaluate the potential of promoter methylation and polymorphism in E-cadherin gene to confer a risk to prostate cancer through meta-analysis. PubMed, Embase, Web of Science, Cochrane Library, and Chinese National Knowledge Infrastructure (CNKI) databases were searched to identify eligible studies published before April 1, 2014. Pooled odds ratios (ORs) with their 95 % confidence intervals (95 % CIs) were calculated by using the random-effect model or the fixed-effect model, according to heterogeneity test. Subgroup analyses were also performed to explore the potential sources of heterogeneity. Sensitivity and publication bias analyses were used to test the robustness of our results. We performed a meta-analysis of 22 included studies, with 11 on -160C/A polymorphism and another 11 on promoter methylation of E-cadherin gene. Our meta-analysis results suggested that E-cadherin -160C/A polymorphism may be a potential risk factor for prostate cancer. Furthermore, we observed that the frequencies of promoter methylation of E-cadherin gene in the prostate cancer tissues were significantly higher than those of normal tissues, indicating that promoter methylation of E-cadherin gene may play an important role in prostate carcinogenesis. In conclusion, the present meta-analysis provides further evidence that promoter methylation and -160C/A polymorphism of E-cadherin gene may confer a risk to prostate cancer. Identifying these risk factors for prostate cancer will improve early detection, allow for selective chemoprevention, and provide further insights into its disease mechanisms.

Association of candidate gene polymorphisms and TGF-beta/IL-10 levels with malaria in three regions of Cameroon: a case-control study

BACKGROUND

Plasmodium falciparum malaria is one of the most widespread and deadliest infectious diseases in children under five years in endemic areas. The disease has been a strong force for evolutionary selection in the human genome, and uncovering the critical host genetic factors that confer resistance to the disease would provide clues to the molecular basis of protective immunity and improve vaccine development initiatives.

METHODS

The effect of single nucleotide polymorphisms (SNPs) and plasma transforming growth factor beta (TGF-β) and interleukin 10 (IL-10) levels on malaria pathology was investigated in a case-control study of 1862 individuals from two major ethnic groups in three regions with intense perennial P. falciparum transmission in Cameroon. Thirty-four malaria candidate polymorphisms, including the sickle cell trait (HbS), were assayed on the Sequenom iPLEX platform while plasma TGF-β and IL-10 levels were measured by sandwich ELISA.

RESULTS

The study confirms the known protective effect of HbS against severe malaria and also reveals a protective effect of SNPs in the nitrogen oxide synthase 2 (NOS2) gene against malaria infection, anaemia and uncomplicated malaria. Furthermore, ADCY9 rs10775349 (additive G) and ABO rs8176746 AC individuals were associated with protection from hyperpyrexia and hyperparasitaemia, respectively. Meanwhile, individuals with the EMR1 rs373533 GT, EMR1 rs461645 CT and RTN3 rs542998 (additive C) genotypes were more susceptible to hyperpyrexia while both females and males with the rs1050828 and rs1050829 SNPs of G6PD, respectively, were more vulnerable to anaemia. Plasma TGF-β levels were strongly correlated with heterozygosity for the ADCY9 rs2230739 and HBB rs334 SNPs while individuals with the ABO rs8176746 AC genotype had lower IL-10 levels.

CONCLUSION

Taken together, this study suggests that some rare polymorphisms in candidate genes may have important implications for the susceptibility of Cameroonians to severe malaria. Moreover using the uncomplicated malaria phenotype may permit the identification of novel pathways in the early development of the disease.

Association of cytokine and Toll-like receptor gene polymorphisms with severe malaria in three regions of Cameroon

P. falciparum malaria is one of the most widespread and deadliest infectious diseases in children under five years in endemic areas. The disease has been a strong force for evolutionary selection in the human genome, and uncovering the critical human genetic factors that confer resistance to the disease would provide clues to the molecular basis of protective immunity that would be invaluable for vaccine development. We investigated the effect of single nucleotide polymorphisms (SNPs) on malaria pathology in a case- control study of 1862 individuals from two major ethnic groups in three regions with intense perennial P. falciparum transmission in Cameroon. Twenty nine polymorphisms in cytokine and toll-like receptor (TLR) genes as well as the sickle cell trait (HbS) were assayed on the Sequenom iPLEX platform. Our results confirm the known protective effect of HbS against severe malaria and also reveal a protective effect of SNPs in interleukin-10 (IL10) cerebral malaria and hyperpyrexia. Furthermore, IL17RE rs708567 GA and hHbS rs334 AT individuals were associated with protection from uncomplicated malaria and anaemia respectively in this study. Meanwhile, individuals with the hHbS rs334 TT, IL10 rs3024500 AA, and IL17RD rs6780995 GA genotypes were more susceptible to severe malarial anaemia, cerebral malaria, and hyperpyrexia respectively. Taken together, our results suggest that polymorphisms in some immune response genes may have important implications for the susceptibility to severe malaria in Cameroonians. Moreover using uncomplicated malaria may allow us to identify novel pathways in the early development of the disease.

DNA repair variants, indoor tanning, and risk of melanoma

Although ultraviolet radiation (UV) exposure from indoor tanning has been linked to an increased risk of melanoma, the role of DNA repair genes in this process is unknown. We evaluated the association of 92 single nucleotide polymorphisms (SNPs) in 20 DNA repair genes with the risk of melanoma and indoor tanning among 929 patients with melanoma and 817 controls from the Minnesota Skin Health Study. Significant associations with melanoma risk were identified for SNPs in ERCC4, ERCC6, RFC1, XPC, MGMT, and FBRSL1 genes; with a cutoff of P < 0.05. ERCC6 and FBRSL1 gene variants and haplotypes interacted with indoor tanning. However, none of the 92 SNPs tested met the correction criteria for multiple comparisons. This study, based on an a priori interest in investigating the role of DNA repair capacity using variants in base excision and nucleotide excision repair, identified several genes that may play a role in resolving UV-induced DNA damage.

IL1RN coding variant is associated with lower risk of acute respiratory distress syndrome and increased plasma IL-1 receptor antagonist

RATIONALE

Acute respiratory distress syndrome (ARDS) behaves as a complex genetic trait, yet knowledge of genetic susceptibility factors remains incomplete.

OBJECTIVES

To identify genetic risk variants for ARDS using large scale genotyping.

METHODS

A multistage genetic association study was conducted of three critically ill populations phenotyped for ARDS. Stage I, a trauma cohort study (n = 224), was genotyped with a 50K gene-centric single-nucleotide polymorphism (SNP) array. We tested SNPs associated with ARDS at P < 5 × 10(-4) for replication in stage II, a trauma case-control population (n = 778). SNPs replicating their association in stage II (P < 0.005) were tested in a stage III nested case-control population of mixed subjects in the intensive care unit (n = 2,063). Logistic regression was used to adjust for potential clinical confounders. We performed ELISA to test for an association between ARDS-associated genotype and plasma protein levels.

MEASUREMENTS AND MAIN RESULTS

A total of 12 SNPs met the stage I threshold for an association with ARDS. rs315952 in the IL1RN gene encoding IL-1 receptor antagonist (IL1RA) replicated its association with reduced ARDS risk in stages II (P < 0.004) and III (P < 0.02), and was robust to clinical adjustment (combined odds ratio = 0.81; P = 4.2 × 10(-5)). Plasma IL1RA level was associated with rs315952C in a subset of critically ill subjects. The effect of rs315952 was independent from the tandem repeat variant in IL1RN.

CONCLUSIONS

The IL1RN SNP rs315952C is associated with decreased risk of ARDS in three populations with heterogeneous ARDS risk factors, and with increased plasma IL1RA response. IL1RA may attenuate ARDS risk.

Genomic scan of selective sweeps in thin and fat tail sheep breeds for identifying of candidate regions associated with fat deposition

BACKGROUND

Identification of genomic regions that have been targets of selection for phenotypic traits is one of the most important and challenging areas of research in animal genetics. However, currently there are relatively few genomic regions identified that have been subject to positive selection. In this study, a genome-wide scan using ~50,000 Single Nucleotide Polymorphisms (SNPs) was performed in an attempt to identify genomic regions associated with fat deposition in fat-tail breeds. This trait and its modification are very important in those countries grazing these breeds.

RESULTS

Two independent experiments using either Iranian or Ovine HapMap genotyping data contrasted thin and fat tail breeds. Population differentiation using FST in Iranian thin and fat tail breeds revealed seven genomic regions. Almost all of these regions overlapped with QTLs that had previously been identified as affecting fat and carcass yield traits in beef and dairy cattle. Study of selection sweep signatures using FST in thin and fat tail breeds sampled from the Ovine HapMap project confirmed three of these regions located on Chromosomes 5, 7 and X. We found increased homozygosity in these regions in favour of fat tail breeds on chromosome 5 and X and in favour of thin tail breeds on chromosome 7.

CONCLUSIONS

In this study, we were able to identify three novel regions associated with fat deposition in thin and fat tail sheep breeds. Two of these were associated with an increase of homozygosity in the fat tail breeds which would be consistent with selection for mutations affecting fat tail size several thousand years after domestication.

Testing departure from Hardy-Weinberg proportions

The Hardy-Weinberg principle, one of the most important principles in population genetics, was originally developed for the study of allele frequency changes in a population over generations. It is now, however, widely used in studies of human diseases to detect inbreeding, populations stratification, and genotyping errors. For assessment of deviation from the Hardy-Weinberg proportions in data, the most popular approaches include the asymptotic Pearson's chi-square goodness-of-fit test and the exact test. The Pearson's chi-square goodness-of-fit test is simple and straightforward, but it is very sensitive to small sample size or rare allele frequency. The exact test of Hardy-Weinberg proportions is preferable in these situations. The exact test can be performed through complete enumeration of heterozygote genotypes or on the basis of the Markov chain Monte Carlo procedure. In this chapter, we describe the Hardy-Weinberg principle and the commonly used Hardy-Weinberg proportions tests and their applications, and we demonstrate how the chi-square test and exact test of Hardy-Weinberg proportions can be performed step-by-step using the popular software programs SAS, R, and PLINK, which have been widely used in genetic association studies, along with numerical examples. We also discuss recent approaches for testing Hardy-Weinberg proportions in case-control study designs that are better than traditional approaches for testing Hardy-Weinberg proportions in controls only. Finally, we note that deviation from the Hardy-Weinberg proportions in affected individuals can provide evidence for an association between genetic variants and diseases.

Genotype calling for the Illumina platform

Genome-wide association studies have been made possible because of advancements in the design of genotyping technologies to assay a million or more single nucleotide polymorphisms (SNPs) simultaneously. This has resulted in the introduction of automated and unsupervised statistical approaches for translating the probe hybridization intensities into the actual genotype calls. This chapter aims to provide an introduction to this process of genotype calling, highlighting in particular the design and approach used for the Illumina BeadArray platforms that are commonly used in large-scale genetic studies. The chapter also provides detailed instructions for preparing the input files required as well as the actual Linux commands and options to execute the ILLUMINUS software. Finally, it concludes with a brief exposition on the different outcomes from genotype calling and the use of perturbation analysis for identifying SNPs with erroneous genotype calls.

A quality control algorithm for filtering SNPs in genome-wide association studies

MOTIVATION

The quality control (QC) filtering of single nucleotide polymorphisms (SNPs) is an important step in genome-wide association studies to minimize potential false findings. SNP QC commonly uses expert-guided filters based on QC variables [e.g. Hardy-Weinberg equilibrium, missing proportion (MSP) and minor allele frequency (MAF)] to remove SNPs with insufficient genotyping quality. The rationale of the expert filters is sensible and concrete, but its implementation requires arbitrary thresholds and does not jointly consider all QC features.

RESULTS

We propose an algorithm that is based on principal component analysis and clustering analysis to identify low-quality SNPs. The method minimizes the use of arbitrary cutoff values, allows a collective consideration of the QC features and provides conditional thresholds contingent on other QC variables (e.g. different MSP thresholds for different MAFs). We apply our method to the seven studies from the Wellcome Trust Case Control Consortium and the major depressive disorder study from the Genetic Association Information Network. We measured the performance of our method compared to the expert filters based on the following criteria: (i) percentage of SNPs excluded due to low quality; (ii) inflation factor of the test statistics (lambda); (iii) number of false associations found in the filtered dataset; and (iv) number of true associations missed in the filtered dataset. The results suggest that with the same or fewer SNPs excluded, the proposed algorithm tends to give a similar or lower value of lambda, a reduced number of false associations, and retains all true associations.

AVAILABILITY

The algorithm is available at http://www4.stat.ncsu.edu/jytzeng/software.php

Using both cases and controls for testing hardy-weinberg proportions in a genetic association study

OBJECTIVES

Assessment of the Hardy-Weinberg proportion (HWP) in controls has been widely used as a quality control measure in case-control association studies. However, when the disease being studied is common, controls might not represent the general population, which could result in inaccurate HWP test results. Such results could lead investigators to discard important single-nucleotide polymorphisms (SNPs) that could potentially be causal. In this paper, we showed the inappropriateness of the HWP test in controls and proposed a mixture HWP (mHWP) exact test using a mixture sample that mimics the general population.

METHODS

The mHWP exact test estimates HWP in a mixture sample that is a combination of both cases and controls proportional to the prevalence of disease. We implemented a re-sampling procedure to construct mixture samples and then obtained the empirical p value of HWP in the general population. Simulation studies were performed to investigate the performance of the proposed mHWP exact test. The method was also applied to a genetic association study of obesity.

RESULTS

The results showed that the mHWP exact test is more likely than either the traditional HWP method in controls or the likelihood-based approach to keep causal SNPs for further analysis when the disease is more common.

CONCLUSION

The mHWP exact test using a mixture sample is a better HWP test for case-control genetic association studies than the traditional HWP in controls or the likelihood-based approach, and it will improve our ability to keep causal SNPs in the case-control genetic association studies.

Genome-wide association studies - A summary for the clinical gastroenterologist

Genome-wide association studies (GWAS) have been applied to various gastrointestinal and liver diseases in recent years. A large number of susceptibility genes and key biological pathways in disease development have been identified. So far, studies in inflammatory bowel diseases, and in particular Crohn’s disease, have been especially successful in defining new susceptibility loci using the GWAS design. The identification of associations related to autophagy as well as several genes involved in immunological response will be important to future research on Crohn’s disease. In this review, key methodological aspects of GWAS, the importance of proper cohort collection, genotyping issues and statistical methods are summarized. Ways of addressing the shortcomings of the GWAS design, when it comes to rare variants, are also discussed. For each of the relevant conditions, findings from the various GWAS are summarized with a focus on the affected biological systems.

Single nucleotide polymorphisms of complement component 5 and periodontitis

BACKGROUND AND OBJECTIVE

Polymorphisms of host defence genes might increase one's risks for periodontitis. This study investigated whether tagging single nucleotide polymorphisms (SNPs) of the gene encoding complement component 5 (C5) are associated with periodontitis in a Hong Kong Chinese population.

MATERIAL AND METHODS

Eleven tagging SNPs of 229 patients with at least moderate periodontitis and 207 control subjects without periodontitis were genotyped using an i-plexGOLD MassARRAY mass-spectrometry system.

RESULTS

Genotype AG of SNP rs17611 was more prevalent in the group of periodontitis patients than in the controls (54.6% vs. 41.7%, p = 0.007). The haplotype CGCA of the haplotype block consisting of rs1035029, rs17611, rs25681 and rs992670 was significantly associated with periodontitis in a dominant model (p = 0.001). The SNP rs17611 showed high linkage disequilibrium with rs1035029, rs25681 and rs992670. Smoking was also significantly associated with periodontitis (p = 0.006).

CONCLUSION

The tagging SNP rs17611 of the C5 gene and smoking may be associated with periodontitis among the Hong Kong Chinese population.

Exploratory data analysis in large-scale genetic studies

Genome-wide association studies (GWAS) have become the method of choice for investigating the genetic basis of common diseases and complex traits. The immense scale of these experiments is unprecedented, involving thousands of samples and up to a million variables. The careful execution of exploratory data analysis (EDA) prior to the actual genotype-phenotype association analysis is crucial as this identifies problematic samples and poorly assayed genetic polymorphisms that, if undetected, can compromise the outcome of the experiment. EDA of such large-scale genetic data sets thus requires specialized numerical and graphical strategies, and this article provides a review of the current exploratory tools commonly used in GWAS.

Recovering unused information in genome-wide association studies: the benefit of analyzing SNPs out of Hardy-Weinberg equilibrium

Although the rapid advancements in high throughput genotyping technology have made genome-wide association studies possible, these studies remain an expensive undertaking, especially when considering the large sample sizes necessary to find the small to moderate effect sizes that define complex diseases. It is therefore prudent to utilize all possible information contained in a genome-wide scan. We propose a straightforward analytical approach that tests often unused SNP data without sacrificing statistical validity. We simulate genotype miscalls under a variety of models consistent with observed miscall rates and test for departures from HWE using the standard Pearson's chi(2)-test. We find that true disease susceptibility loci subjected to various patterns of genotype miscalls can be largely out of HWE and, thus, be candidates for removal before association testing. These loci, we demonstrate, can maintain sufficient statistical power even under extreme error models. We additionally show that random miscalls of null SNPs, independent of the phenotype, do not induce bias in case-control or cohort studies, and we suggest that a significant HWE test should not prevent a SNP from being tested when conducting genome-wide association studies in these scenarios. However, association findings for SNPs that are out of HWE must be treated more carefully than 'regular' findings, for example, by re-genotyping the SNP in the same study using a different genotyping technology.

A genetic association study in the Gambia using tagging polymorphisms in the major histocompatibility complex class III region implicates a HLA-B associated transcript 2 polymorphism in severe malaria susceptibility

The tumour necrosis factor (TNF) gene and other genes flanking it in the major histocompatibility complex (MHC) class III region are potentially important mediators of both immunity and pathogenesis of malaria. We investigated the association of severe malaria with 11 haplotype tagging-polymorphisms for 11 MHC class III candidate genes, including TNF, lymphotoxin alpha (LTA), allograft inflammatory factor 1 (AIF1), and HLA-B associated transcript 2 (BAT2). An analysis of 2,162 case-controls demonstrated the first evidence of association between a BAT2 polymorphism (rs1046089) and severe malaria.

Impact of genotyping errors on the type I error rate and the power of haplotype-based association methods

Background

We investigated the influence of genotyping errors on the type I error rate and empirical power of two haplotype based association methods applied to candidate regions. We compared the performance of the Mantel Statistic Using Haplotype Sharing and the haplotype frequency based score test with that of the Armitage trend test.

Our study is based on 1000 replication of simulated case-control data settings with 500 cases and 500 controls, respectively. One of the examined markers was set to be the disease locus with a simulated odds ratio of 3. Differential and non-differential genotyping errors were introduced following a misclassification model with varying mean error rates per locus in the range of 0.2% to 15.6%.

Results

We found that the type I error rate of all three test statistics hold the nominal significance level in the presence of nondifferential genotyping errors and low error rates. For high and differential error rates, the type I error rate of all three test statistics was inflated, even when genetic markers not in Hardy-Weinberg Equilibrium were removed. The empirical power of all three association test statistics remained high at around 89% to 94% when genotyping error rates were low, but decreased to 48% to 80% for high and nondifferential genotyping error rates.

Conclusion

Currently realistic genotyping error rates for candidate gene analysis (mean error rate per locus of 0.2%) pose no significant problem for the type I error rate as well as the power of all three investigated test statistics.

Lack of association of interferon regulatory factor 1 with severe malaria in affected child-parental trio studies across three African populations

Interferon Regulatory Factor 1 (IRF-1) is a member of the IRF family of transcription factors, which have key and diverse roles in the gene-regulatory networks of the immune system. IRF-1 has been described as a critical mediator of IFN-gamma signalling and as the major player in driving TH1 type responses. It is therefore likely to be crucial in both innate and adaptive responses against intracellular pathogens such as Plasmodium falciparum. Polymorphisms at the human IRF1 locus have been previously found to be associated with the ability to control P. falciparum infection in populations naturally exposed to malaria. In order to test whether genetic variation at the IRF1 locus also affects the risk of developing severe malaria, we performed a family-based test of association for 18 Single Nucleotide Polymorphisms (SNPs) across the gene in three African populations, using genotype data from 961 trios consisting of one affected child and his/her two parents (555 from The Gambia, 204 from Kenya and 202 from Malawi). No significant association with severe malaria or severe malaria subphenotypes (cerebral malaria and severe malaria anaemia) was observed for any of the SNPs/haplotypes tested in any of the study populations. Our results offer no evidence that the molecular pathways regulated by the transcription factor IRF-1 are involved in the immune-based pathogenesis of severe malaria.

Deviations from Hardy-Weinberg proportions for multiple alleles under viability selection

Departures of genotype frequencies from Hardy-Weinberg proportions (HWP) for a single autosomal locus due to viability selection in a random mating population have been studied only for the two-allele case. In this article, the analysis of deviations from HWP due to constant viability selection is extended to multiple alleles. The deviations for an autosomal locus with k alleles are measured by means of k fii fixation indices for homozygotes and k(k-1)/2 fij fixation indices for heterozygotes, and expressions are obtained for these indices (FIS statistics) under the multiallele viability model. Furthermore, expressions for fii and fij when the multiallele polymorphism is at stable equilibrium are also derived and it is demonstrated that the pattern of multiallele Hardy-Weinberg deviations at equilibrium is characterized by a global heterozygote excess and a deficiency of each of the homozygotes. This pattern may be useful for detecting whether a given multiallelic polymorphism is at stable equilibrium in the population due to viability selection. An analysis of Hardy-Weinberg deviations from published data for the three-allele polymorphism at the beta-globin locus in human populations from West Africa is presented for illustration.

Perturbation analysis: a simple method for filtering SNPs with erroneous genotyping in genome-wide association studies

We introduce a simple and yet scientifically objective criterion for identifying SNPs with genotyping errors due to poor clustering. This yields a metric for assessing the stability of the assigned genotypes by evaluating the extent of discordance between the calls made with the unperturbed and perturbed intensities. The efficacy of the metric is evaluated by: (1) estimating the extent of over-dispersion of the Hardy-Weinberg equilibrium chi-square test statistics; (2) an interim case-control study, where we investigated the efficacy of the introduced metric and standard quality control filters in reducing the number of SNPs with evidence of phenotypic association which are attributed to genotyping errors; (3) investigating the call and concordance rates of SNPs identified by perturbation analysis which have been genotyped on both Affymetrix and Illumina platforms. Removing SNPs identified by the extent of discordance can reduce the degree of over-dispersion of the HWE test statistic. Sensible use of perturbation analysis in an association study can correctly identify SNPs with problematic genotyping, reducing the number required for visual inspection. SNPs identified by perturbation analysis had lower call and concordance rates, and removal of these SNPs significantly improved the performance for the remaining SNPs.

Common statistical issues in genome-wide association studies: a review on power, data quality control, genotype calling and population structure

PURPOSE OF REVIEW

Genetic association studies which survey the entire genome have become a common design for uncovering the genetic basis of common diseases, including lipid-related traits. Such studies have identified several novel loci which influence blood lipids. The present review highlights the statistical challenges associated with such large-scale genetic studies and discusses the available methodological strategies for handling these issues.

RECENT FINDINGS

The successful analysis of genome-wide data assayed on commercial genotyping arrays depends on careful exploration of the data. Unaccounted sample failures, genotyping errors and population structure can introduce misleading signals that mimic genuine association. Careful interpretation of useful summary statistics and graphical data displays can minimize the extent of false associations that need to be followed up in replication or fine-mapping experiments.

SUMMARY

Recently published genome-wide studies are beginning to yield valuable insights into the importance of well designed methodological and statistical techniques for sensible interpretation of the plethora of genetic data generated.