Gains in power for exhaustive analyses of haplotypes using variable-sized sliding window strategy: a comparison of association-mapping strategies

Analysis of dog breed diversity using a composite selection index

During breed development, domestic dogs have undergone genetic bottlenecks and sustained selective pressures, as a result distinctive genomic diversity occurs to varying degrees within and between breed groups. This diversity can be identified using standard methods or combinations of these methods. This study explored the application of a combined selection index, composite selection signals (CSS), derived from multiple methods to an existing genotype dataset from three breed groups developed in distinct regions of Asia: Qinghai-Tibet plateau dogs (adapted to living at altitude), Xi dogs (with superior running ability) and Mountain hounds (used for hunting ability). The CSS analysis confirmed top ranked genomic regions on CFA10 and CFA21 in Qinghai-Tibet plateau dogs, CFA1 in Xi dogs and CFA5 in Mountain hounds. CSS analysis identified additional significant genomic regions in each group, defined by a total of 1,397, 1,475 and 1,675 significant SNPs in the Qinghai-Tibetan Plateau dogs, Xi dogs and Mountain hounds, respectively. Chitinase 3 Like 1 (CHI3L1) and Leucine Rich Repeat Containing G Protein-Coupled Receptor 6 (LGR6) genes were located in the top ranked region on CFA7 (0.02-1 Mb) in the Qinghai-Tibetan Plateau dogs. Both genes have been associated with hypoxia responses or altitude adaptation in humans. For the Xi dogs, the top ranked region on CFA25 contained the Transient Receptor Potential Cation Channel Subfamily C Member 4 (TRPC4) gene. This calcium channel is important for optimal muscle performance during exercise. The outstanding signals in the Mountain dogs were on CFA5 with 213 significant SNPs that spanned genes involved in cardiac development, sight and generation of biochemical energy. These findings support the use of the combined index approach for identifying novel regions of genome diversity in dogs. As with other methods, the results do not prove causal links between these regions and phenotypes, but they may assist in focusing future studies that seek to identify functional pathways that contribute to breed diversity.

Haplotype-Based Single-Step GWAS for Yearling Temperament in American Angus Cattle

Behavior is a complex trait and, therefore, understanding its genetic architecture is paramount for the development of effective breeding strategies. The objective of this study was to perform traditional and weighted single-step genome-wide association studies (ssGWAS and WssGWAS, respectively) for yearling temperament (YT) in North American Angus cattle using haplotypes. Approximately 266 K YT records and 70 K animals genotyped using a 50 K single nucleotide polymorphisms (SNP) panel were used. Linkage disequilibrium thresholds (LD) of 0.15, 0.50, and 0.80 were used to create the haploblocks, and the inclusion of non-LD-clustered SNPs (NCSNP) with the haplotypes in the genomic models was also evaluated. WssGWAS did not perform better than ssGWAS. Cattle YT was found to be a highly polygenic trait, with genes and quantitative trait loci (QTL) broadly distributed across the whole genome. Association studies using LD-based haplotypes should include NCSNPs and different LD thresholds to increase the likelihood of finding the relevant genomic regions affecting the trait of interest. The main candidate genes identified, i.e., ATXN10, ADAM10, VAX2, ATP6V1B1, CRISPLD1, CAPRIN1, FA2H, SPEF2, PLXNA1, and CACNA2D3, are involved in important biological processes and metabolic pathways related to behavioral traits, social interactions, and aggressiveness in cattle. Future studies should further investigate the role of these candidate genes.

Status and prospects of genome-wide association studies in plants

Genome-wide association studies (GWAS) have developed into a powerful and ubiquitous tool for the investigation of complex traits. In large part, this was fueled by advances in genomic technology, enabling us to examine genome-wide genetic variants across diverse genetic materials. The development of the mixed model framework for GWAS dramatically reduced the number of false positives compared with naïve methods. Building on this foundation, many methods have since been developed to increase computational speed or improve statistical power in GWAS. These methods have allowed the detection of genomic variants associated with either traditional agronomic phenotypes or biochemical and molecular phenotypes. In turn, these associations enable applications in gene cloning and in accelerated crop breeding through marker assisted selection or genetic engineering. Current topics of investigation include rare-variant analysis, synthetic associations, optimizing the choice of GWAS model, and utilizing GWAS results to advance knowledge of biological processes. Ongoing research in these areas will facilitate further advances in GWAS methods and their applications.

A Genome-Wide Association Study on Feed Efficiency Related Traits in Landrace Pigs

Feed efficiency (FE) traits in pigs are of utmost economic importance. Genetic improvement of FE related traits in pigs might significantly reduce production cost and energy consumption. Hence, our study aimed at identifying SNPs and candidate genes associated with FE related traits, including feed conversion ratio (FCR), average daily gain (ADG), average daily feed intake (ADFI), and residual feed intake (RFI). A genome-wide association study (GWAS) was performed for the four FE related traits in 296 Landrace pigs genotyped with PorcineSNP50 BeadChip. Two different single-trait methods, single SNP linear model GWAS (LM-GWAS) and single-step GWAS (ssGWAS), were implemented. Our results showed that the two methods showed high consistency with respect to SNP identification. A total of 32 common significant SNPs associated with the four FE related traits were identified. Bioinformatics analysis revealed eight common QTL regions, of which three QTL regions related to ADFI and RFI traits were overlapped. Gene ontology analysis revealed six common candidate genes (PRELID2, GPER1, PDX1, TEX2, PLCL2, ICAM2) relevant for the four FE related traits. These genes are involved in the processes of fat synthesis and decomposition, lipid transport process, insulin metabolism, among others. Our results provide, new insights into the genetic mechanisms and candidate function genes of FE related traits in pigs. However, further investigations to validate these results are warranted.

A Genome-Wide Association Study for Calving Interval in Holstein Dairy Cows Using Weighted Single-Step Genomic BLUP Approach

The aim of the present study was to identify genomic region(s) associated with the length of the calving interval in primiparous (n = 6866) and multiparous (n = 5071) Holstein cows. The single nucleotide polymorphism (SNP) solutions were estimated using a weighted single-step genomic best linear unbiased prediction (WssGBLUP) approach and imputed high-density panel (777 k) genotypes. The effects of markers and the genomic estimated breeding values (GEBV) of the animals were obtained by five iterations of WssGBLUP. The results showed that the accuracies of GEBVs with WssGBLUP improved by +5.4 to +5.7, (primiparous cows) and +9.4 to +9.7 (multiparous cows) percent points over accuracies from the pedigree-based BLUP. The most accurate genomic evaluation was provided at the second iteration of WssGBLUP, which was used to identify associated genomic regions using a windows-based GWAS procedure. The proportion of additive genetic variance explained by windows of 50 consecutive SNPs (with an average of 165 Kb) was calculated and the region(s) that accounted for equal to or more than 0.20% of the total additive genetic variance were used to search for candidate genes. Three windows of 50 consecutive SNPs (BTA3, BTA6, and BTA7) were identified to be associated with the length of the calving interval in primi- and multiparous cows, while the window with the highest percentage of explained genetic variance was located on BTA3 position 49.42 to 49.52 Mb. There were five genes including ARHGAP29, SEC24D, METTL14, SLC36A2, and SLC36A3 inside the windows associated with the length of the calving interval. The biological process terms including alanine transport, L-alanine transport, proline transport, and glycine transport were identified as the most important terms enriched by the genes inside the identified windows.

Exploring effective approaches for haplotype block phasing

BACKGROUND

Knowledge of phase, the specific allele sequence on each copy of homologous chromosomes, is increasingly recognized as critical for detecting certain classes of disease-associated mutations. One approach for detecting such mutations is through phased haplotype association analysis. While the accuracy of methods for phasing genotype data has been widely explored, there has been little attention given to phasing accuracy at haplotype block scale. Understanding the combined impact of the accuracy of phasing tool and the method used to determine haplotype blocks on the error rate within the determined blocks is essential to conduct accurate haplotype analyses.

RESULTS

We present a systematic study exploring the relationship between seven widely used phasing methods and two common methods for determining haplotype blocks. The evaluation focuses on the number of haplotype blocks that are incorrectly phased. Insights from these results are used to develop a haplotype estimator based on a consensus of three tools. The consensus estimator achieved the most accurate phasing in all applied tests. Individually, EAGLE2, BEAGLE and SHAPEIT2 alternate in being the best performing tool in different scenarios. Determining haplotype blocks based on linkage disequilibrium leads to more correctly phased blocks compared to a sliding window approach. We find that there is little difference between phasing sections of a genome (e.g. a gene) compared to phasing entire chromosomes. Finally, we show that the location of phasing error varies when the tools are applied to the same data several times, a finding that could be important for downstream analyses.

CONCLUSIONS

The choice of phasing and block determination algorithms and their interaction impacts the accuracy of phased haplotype blocks. This work provides guidance and evidence for the different design choices needed for analyses using haplotype blocks. The study highlights a number of issues that may have limited the replicability of previous haplotype analysis.

Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle

Background

Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness.

Results

The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes.

Conclusions

GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0713-4) contains supplementary material, which is available to authorized users.

Single Marker and Haplotype-Based Association Analysis of Semolina and Pasta Colour in Elite Durum Wheat Breeding Lines Using a High-Density Consensus Map

Association mapping is usually performed by testing the correlation between a single marker and phenotypes. However, because patterns of variation within genomes are inherited as blocks, clustering markers into haplotypes for genome-wide scans could be a worthwhile approach to improve statistical power to detect associations. The availability of high-density molecular data allows the possibility to assess the potential of both approaches to identify marker-trait associations in durum wheat. In the present study, we used single marker- and haplotype-based approaches to identify loci associated with semolina and pasta colour in durum wheat, the main objective being to evaluate the potential benefits of haplotype-based analysis for identifying quantitative trait loci. One hundred sixty-nine durum lines were genotyped using the Illumina 90K Infinium iSelect assay, and 12,234 polymorphic single nucleotide polymorphism (SNP) markers were generated and used to assess the population structure and the linkage disequilibrium (LD) patterns. A total of 8,581 SNPs previously localized to a high-density consensus map were clustered into 406 haplotype blocks based on the average LD distance of 5.3 cM. Combining multiple SNPs into haplotype blocks increased the average polymorphism information content (PIC) from 0.27 per SNP to 0.50 per haplotype. The haplotype-based analysis identified 12 loci associated with grain pigment colour traits, including the five loci identified by the single marker-based analysis. Furthermore, the haplotype-based analysis resulted in an increase of the phenotypic variance explained (50.4% on average) and the allelic effect (33.7% on average) when compared to single marker analysis. The presence of multiple allelic combinations within each haplotype locus offers potential for screening the most favorable haplotype series and may facilitate marker-assisted selection of grain pigment colour in durum wheat. These results suggest a benefit of haplotype-based analysis over single marker analysis to detect loci associated with colour traits in durum wheat.

Loci, genes, and mechanisms associated with tolerance to ferrous iron toxicity in rice (Oryza sativa L.)

A genome-wide association study in rice yielded loci and candidate genes associated with tolerance to iron toxicity, and revealed biochemical mechanisms associated with tolerance in contrasting haplotypes. Iron toxicity is a major nutrient disorder affecting rice. Therefore, understanding the genetic and physiological mechanisms associated with iron toxicity tolerance is crucial in adaptive breeding and biofortification. We conducted a genome-wide association study (GWAS) by exposing a population of 329 accessions representing all subgroups of rice to ferrous iron stress (1000 ppm, 5 days). Expression patterns and sequence polymorphisms of candidate genes were investigated, and physiological hypotheses related to candidate loci were tested using a subset of contrasting haplotypes. Both iron including and excluding tolerant genotypes were observed, and shoot iron concentrations explained around 15.5 % of the variation in foliar symptom formation. GWAS for seven traits yielded 20 SNP markers exceeding a significance threshold of -log10 P > 4.0, which represented 18 distinct loci. One locus mapped for foliar symptom formation on chromosome 1 contained two putative glutathione-S-transferases, which were strongly expressed under iron stress and showed sequence polymorphisms in complete linkage disequilibrium with the most significant SNP. Contrasting haplotypes for this locus showed significant differences in dehydroascorbate reductase activity, which affected the plants' redox status under iron stress. We conclude that maintaining foliar redox homeostasis under iron stress represented an important tolerance mechanism associated with a locus identified through GWAS.

Comparison of haplotype-based statistical tests for disease association with rare and common variants

Recent literature has highlighted the advantages of haplotype association methods for detecting rare variants associated with common diseases. As several new haplotype association methods have been proposed in the past few years, a comparison of new and standard methods is important and timely for guidance to the practitioners. We consider nine methods-Haplo.score, Haplo.glm, Hapassoc, Bayesian hierarchical Generalized Linear Model (BhGLM), Logistic Bayesian LASSO (LBL), regularized GLM (rGLM), Haplotype Kernel Association Test, wei-SIMc-matching and Weighted Haplotype and Imputation-based Tests. These can be divided into two types-individual haplotype-specific tests and global tests depending on whether there is just one overall test for a haplotype region (global) or there is an individual test for each haplotype in the region. Haplo.score is the only method that tests for both; Haplo.glm, Hapassoc, BhGLM and LBL are individual haplotype-specific, while the rest are global tests. For comparison, we also apply a popular collapsing method-Sequence Kernel Association Test (SKAT) and its two variants-SKAT-O (Optimal) and SKAT-C (Combined). We carry out an extensive comparison on our simulated data sets as well as on the Genetic Analysis Workshop (GAW) 18 simulated data. Further, we apply the methods to GAW18 real hypertension data and Dallas Heart Study sequence data. We find that LBL, Haplo.score (global test) and rGLM perform well over the scenarios considered here. Also, haplotype methods are more powerful (albeit more computationally intensive) than SKAT and its variants in scenarios where multiple causal variants act interactively to produce haplotype effects.

Genetic association between germline JAK2 polymorphisms and myeloproliferative neoplasms in Hong Kong Chinese population: a case-control study

BACKGROUND

Myeloproliferative neoplasms (MPNs) are a group of haematological malignancies that can be characterised by a somatic mutation (JAK2V617F). This mutation causes the bone marrow to produce excessive blood cells and is found in polycythaemia vera (~95%), essential thrombocythaemia and primary myelofibrosis (both ~50%). It is considered as a major genetic factor contributing to the development of these MPNs. No genetic association study of MPN in the Hong Kong population has so far been reported. Here, we investigated the relationship between germline JAK2 polymorphisms and MPNs in Hong Kong Chinese to find causal variants that contribute to MPN development. We analysed 19 tag single nucleotide polymorphisms (SNPs) within the JAK2 locus in 172 MPN patients and 470 healthy controls. Three of these 19 SNPs defined the reported JAK2 46/1 haplotype: rs10974944, rs12343867 and rs12340895. Allele and haplotype frequencies were compared between patients and controls by logistic regression adjusted for sex and age. Permutation test was used to correct for multiple comparisons. With significant findings from the 19 SNPs, we then examined 76 additional SNPs across the 148.7-kb region of JAK2 via imputation with the SNP data from the 1000 Genomes Project.

RESULTS

In single-marker analysis, 15 SNPs showed association with JAK2V617F-positive MPNs (n = 128), and 8 of these were novel MPN-associated SNPs not previously reported. Exhaustive variable-sized sliding-window haplotype analysis identified 184 haplotypes showing significant differences (P < 0.05) in frequencies between patients and controls even after multiple-testing correction. However, single-marker alleles exhibited the strongest association with V617F-positive MPNs. In local Hong Kong Chinese, rs12342421 showed the strongest association signal: asymptotic P = 3.76 × 10-15, empirical P = 2.00 × 10-5 for 50,000 permutations, OR = 3.55 for the minor allele C, and 95% CI, 2.59-4.87. Conditional logistic regression also signified an independent effect of rs12342421 in significant haplotype windows, and this independent effect remained unchanged even with the imputation of additional 76 SNPs. No significant association was found between V617F-negative MPNs and JAK2 SNPs.

CONCLUSION

With a large sample size, we reported the association between JAK2V617F-positive MPNs and 15 tag JAK2 SNPs and the association of rs12342421 being independent of the JAK2 46/1 haplotype in Hong Kong Chinese population.

Genetic analysis of axial length genes in high grade myopia from Indian population

Purpose

To study the putative association of Membrane frizzled related protein (MFRP) and Visual system homeobox protein (VSX2) gene variants with axial length (AL) in myopia.

Method

A total of 189 samples with (N = 98) and without (N = 91) myopia were genotyped for the MRFP and VSX2 variations in ABI Prism 3100 AVANT genetic analyzer. Genotype/haplotype analysis was performed using PLINK, Haploview and THESIAS softwares.

Results

Fifteen variations were observed in the MFRP gene of which, rs36015759 (c.492C > T, T164T) in exon 5 was distributed at a high frequency in the controls and significantly associated with a low risk for myopia (P = 4.10 ∗ e^− 07 OR < 1.0). An increased frequency for the coding haplotype block [CGTCGG] harboring rs36015759 was observed in controls (31%) than cases (8%) that also correlated with a decreased mean AL (− 1.35085; P = 0.000444) by THESIAS analysis. The ‘T’ allele of rs36015759 was predicted to abolish the binding site for splicing enhancer (SRp40) by FASTSNP analysis.

Conclusion

Myopia is a complex disorder influenced by genetic and environmental factors. Our work shows evidence of association of a specific MFRP haplotype which was more prevalent in controls with decreased AL. However, replication and functional studies are warranted to confirm these findings.

Single nucleotide polymorphisms and haplotypes associated with feed efficiency in beef cattle

BACKGROUND

General, breed- and diet-dependent associations between feed efficiency in beef cattle and single nucleotide polymorphisms (SNPs) or haplotypes were identified on a population of 1321 steers using a 50 K SNP panel. Genomic associations with traditional two-step indicators of feed efficiency - residual feed intake (RFI), residual average daily gain (RADG), and residual intake gain (RIG) - were compared to associations with two complementary one-step indicators of feed efficiency: efficiency of intake (EI) and efficiency of gain (EG). Associations uncovered in a training data set were evaluated on independent validation data set. A multi-SNP model was developed to predict feed efficiency. Functional analysis of genes harboring SNPs significantly associated with feed efficiency and network visualization aided in the interpretation of the results.

RESULTS

For the five feed efficiency indicators, the numbers of general, breed-dependent, and diet-dependent associations with SNPs (P-value < 0.0001) were 31, 40, and 25, and with haplotypes were six, ten, and nine, respectively. Of these, 20 SNP and six haplotype associations overlapped between RFI and EI, and five SNP and one haplotype associations overlapped between RADG and EG. This result confirms the complementary value of the one and two-step indicators. The multi-SNP models included 89 SNPs and offered a precise prediction of the five feed efficiency indicators. The associations of 17 SNPs and 7 haplotypes with feed efficiency were confirmed on the validation data set. Nine clusters of Gene Ontology and KEGG pathway categories (mean P-value < 0.001) including, 9nucleotide binding; ion transport, phosphorous metabolic process, and the MAPK signaling pathway were overrepresented among the genes harboring the SNPs associated with feed efficiency.

CONCLUSIONS

The general SNP associations suggest that a single panel of genomic variants can be used regardless of breed and diet. The breed- and diet-dependent associations between SNPs and feed efficiency suggest that further refinement of variant panels require the consideration of the breed and management practices. The unique genomic variants associated with the one- and two-step indicators suggest that both types of indicators offer complementary description of feed efficiency that can be exploited for genome-enabled selection purposes.

Haplotype kernel association test as a powerful method to identify chromosomal regions harboring uncommon causal variants

For most complex diseases, the fraction of heritability that can be explained by the variants discovered from genome-wide association studies is minor. Although the so-called "rare variants" (minor allele frequency [MAF] < 1%) have attracted increasing attention, they are unlikely to account for much of the "missing heritability" because very few people may carry these rare variants. The genetic variants that are likely to fill in the "missing heritability" include uncommon causal variants (MAF < 5%), which are generally untyped in association studies using tagging single-nucleotide polymorphisms (SNPs) or commercial SNP arrays. Developing powerful statistical methods can help to identify chromosomal regions harboring uncommon causal variants, while bypassing the genome-wide or exome-wide next-generation sequencing. In this work, we propose a haplotype kernel association test (HKAT) that is equivalent to testing the variance component of random effects for distinct haplotypes. With an appropriate weighting scheme given to haplotypes, we can further enhance the ability of HKAT to detect uncommon causal variants. With scenarios simulated according to the population genetics theory, HKAT is shown to be a powerful method for detecting chromosomal regions harboring uncommon causal variants.

Insulin-like growth factor 1 is not associated with high myopia in a large Japanese cohort

PURPOSE

To investigate whether genetic variations in the insulin-like growth factor 1 (IGF-1) gene are associated with high myopia in Japanese.

METHODS

A total of 1,339 unrelated Japanese patients with high myopia (axial length ≥26 mm in both eyes) and two independent control groups were evaluated (334 cataract patients without high myopia and 1,194 healthy Japanese individuals). The mean axial length (mm±SD) in the case group was 29.18±1.85 mm, and the mean spherical equivalent (D±SD) of the phakic eyes was -12.69±4.54 D. We genotyped five tagging single nucleotide polymorphisms (SNPs) in IGF-1: rs6214, rs978458, rs5742632, rs12423791, and rs2162679. Chi-square tests for trend, multivariable logistic regression, and haplotype regression analysis were conducted.

RESULTS

We found no significant association between the IGF-1 SNPs and high or extreme myopia (axial length ≥28 mm in both eyes, 837 subjects) in the additive model, even when compared with the cataract and general population controls, with or without adjustments for age and sex. The evaluation using dominant and recessive models also did not reveal any significant associations. The haplotype analysis with a variable-sized sliding-window strategy also showed a lack of association of IGF-1 SNPs with high or extreme myopia.

CONCLUSIONS

The results of the present study using a Japanese subset do not support the proposal that the IGF-1 gene determines susceptibility to high or extreme myopia in Caucasians and Chinese. Further studies are needed to confirm our reports in other populations and to identify the underlying genetic determinants of these ocular pathological conditions.

Genetic susceptibility to refractive error: association of vasoactive intestinal peptide receptor 2 (VIPR2) with high myopia in Chinese

Myopia is the most common ocular disease worldwide. We investigated the association of high myopia with the common single nucleotide polymorphisms (SNPs) of five candidate genes – early growth response 1 (EGR1), v-fos FBJ murine osteosarcoma viral oncogene homolog (FOS), jun oncogene (JUN), vasoactive intestinal peptide (VIP), and vasoactive intestinal peptide receptor 2 (VIPR2). We recruited 1200 unrelated Chinese subjects with 600 cases (spherical equivalent ≤−8.00 diopters) and 600 controls (spherical equivalent within ±1.00 diopter). A discovery sample set was formed from 300 cases and 300 controls, and a replication sample set from the remaining samples. Tag SNPs were genotyped for the discovery sample set, and the most significant haplotypes and their constituent SNPs were followed up with the replication sample set. The allele and haplotype frequencies in cases and controls were compared by logistic regression adjusted for sex and age to give P_a values, and multiple comparisons were corrected by permutation test to give P_aemp values. Odd ratios (OR) were calculated accordingly. In the discovery phase, EGR1, JUN and VIP did not show any significant association while FOS and VIPR2 demonstrated significant haplotype association with high myopia. In the replication phase, the haplotype association for VIPR2 was successfully replicated, but not FOS. In analysis combining both sample sets, the most significant association signals of VIPR2 were the single marker rs2071625 (P_a = 0.0008, P_aemp = 0.0046 and OR = 0.75) and the 4-SNP haplotype window rs2071623-rs2071625-rs2730220-rs885863 (omnibus test, P_a = 9.10e-10 and P_aemp = 0.0001) with one protective haplotype (GGGG: P_aemp = 0.0002 and OR = 0.52) and one high-risk haplotype (GAGA: P_aemp = 0.0027 and OR = 4.68). This 4-SNP haplotype window was the most significant in all sample sets examined. This is the first study to suggest a role of VIPR2 in the genetic susceptibility to high myopia. EGR1, JUN, FOS and VIP are unlikely to be important in predisposing humans to high myopia.

A genome-wide scan for breast cancer risk haplotypes among African American women

Genome-wide association studies (GWAS) simultaneously investigating hundreds of thousands of single nucleotide polymorphisms (SNP) have become a powerful tool in the investigation of new disease susceptibility loci. Haplotypes are sometimes thought to be superior to SNPs and are promising in genetic association analyses. The application of genome-wide haplotype analysis, however, is hindered by the complexity of haplotypes themselves and sophistication in computation. We systematically analyzed the haplotype effects for breast cancer risk among 5,761 African American women (3,016 cases and 2,745 controls) using a sliding window approach on the genome-wide scale. Three regions on chromosomes 1, 4 and 18 exhibited moderate haplotype effects. Furthermore, among 21 breast cancer susceptibility loci previously established in European populations, 10p15 and 14q24 are likely to harbor novel haplotype effects. We also proposed a heuristic of determining the significance level and the effective number of independent tests by the permutation analysis on chromosome 22 data. It suggests that the effective number was approximately half of the total (7,794 out of 15,645), thus the half number could serve as a quick reference to evaluating genome-wide significance if a similar sliding window approach of haplotype analysis is adopted in similar populations using similar genotype density.

Localization of association signal from risk and protective variants in sequencing studies

Aggregating information across multiple variants in a gene or region can improve power for rare variant association testing. Power is maximized when the aggregation region contains many causal variants and few neutral variants. In this paper, we present a method for the localization of the association signal in a region using a sliding-window based approach to rare variant association testing in a region. We first introduce a novel method for analysis of rare variants, the Difference in Minor Allele Frequency test (DMAF), which allows combined analysis of common and rare variants, and makes no assumptions about the direction of effects. In whole-region analyses of simulated data with risk and protective variants, DMAF and other methods which pool data across individuals were found to outperform methods which pool data across variants. We then implement a sliding-window version of DMAF, using a step-down permutation approach to control type I error with the testing of multiple windows. In simulations, the sliding-window DMAF improved power to detect a causal sub-region, compared to applying DMAF to the whole region. Sliding-window DMAF was also effective in localizing the causal sub-region. We also applied the DMAF sliding-window approach to test for an association between response to the drug gemcitabine and variants in the gene FKBP5 sequenced in 91 lymphoblastoid cell lines derived from white non-Hispanic individuals. The application of the sliding-window test procedure detected an association in a sub-region spanning an exon and two introns, when rare and common variants were analyzed together.

Investigating the relationship between UMODL1 gene polymorphisms and high myopia: a case-control study in Chinese

Background

The UMODL1 gene was found to be associated with high myopia in Japanese. This study aimed to investigate this gene for association with high myopia in Chinese.

Methods

Two groups of unrelated Han Chinese from Hong Kong were recruited using the same criteria: Sample Set 1 comprising 356 controls (spherical equivalent, SE, within ±1 diopter or D) and 356 cases (SE ≤ −8D), and Sample Set 2 comprising 394 controls and 526 cases. Fifty-nine tag single nucleotide polymorphisms (SNPs) were selected and genotyped for Sample Set 1. Four SNPs were followed up with Sample Set 2. Both single-marker and haplotype analyses were performed with cases defined by different SE thresholds. Secondary phenotypes were also analyzed for association with genotypes.

Results

Data filtering left 57 SNPs for analysis. Single-marker analysis did not reveal any significant differences between cases and controls in the initial study. However, haplotype GCT for markers rs220168-rs220170-rs11911271 showed marginal significance (empirical P = 0.076; SE ≤ −12D for cases), but could not be replicated in the follow-up study. In contrast, non-synonymous SNP rs3819142 was associated with high myopia (SE ≤ −10D) in the follow-up study, but could not be confirmed using Sample Set 1. The SNP rs2839471, positive in the original Japanese study, gave negative results in all our analyses. Exploratory analysis of secondary phenotypes indicated that allele C of rs220120 was associated with anterior chamber depth (adjusted P = 0.0460).

Conclusions

Common UMODL1 polymorphisms were unlikely to be important in the genetic susceptibility to high myopia in Han Chinese.

Similarity-based multimarker association tests for continuous traits

Testing multiple markers simultaneously not only can capture the linkage disequilibrium patterns but also can decrease the number of tests and thus alleviate the multiple-testing penalty. If a gene is associated with a phenotype, subjects with similar genotypes in this gene should also have similar phenotypes. Based on this concept, we have developed a general framework that is applicable to continuous traits. Two similarity-based tests (namely, SIMc and SIMp tests) were derived as special cases of the general framework. In our simulation study, we compared the power of the two tests with that of the single-marker analysis, a standard haplotype regression, and a popular and powerful kernel machine regression. Our SIMc test outperforms other tests when the average R(2) (a measure of linkage disequilibrium) between the causal variant and the surrounding markers is larger than 0.3 or when the causal allele is common (say, frequency = 0.3). Our SIMp test outperforms other tests when the causal variant was introduced at common haplotypes (the maximum frequency of risk haplotypes >0.4). We also applied our two tests to an adiposity data set to show their utility.

PAX6 haplotypes are associated with high myopia in Han chinese

Background

The paired box 6 (PAX6) gene is considered as a master gene for eye development. Linkage of myopia to the PAX6 region on chromosome 11p13 was shown in several studies, but the results for association between myopia and PAX6 were inconsistent so far.

Methodology/Principal Findings

We genotyped 16 single nucleotide polymorphisms (SNPs) in the PAX6 gene and its regulatory regions in an initial study for 300 high myopia cases and 300 controls (Group 1), and successfully replicated the positive results with another independent group of 299 high myopia cases and 299 controls (Group 2). Five SNPs were genotyped in the replication study. The spherical equivalent of subjects with high myopia was ≤−8.0 dioptres. The PLINK package was used for genetic data analysis. No association was found between each of the SNPs and high myopia. However, exhaustive sliding-window haplotype analysis highlighted an important role for rs12421026 because haplotypes containing this SNP were found to be associated with high myopia. The most significant results were given by the 4-SNP haplotype window consisting of rs2071754, rs3026393, rs1506 and rs12421026 (P = 3.54×10⁻¹⁰, 4.06×10⁻¹¹ and 1.56×10⁻¹⁸ for Group 1, Group 2 and Combined Group, respectively) and the 3-SNP haplotype window composed of rs3026393, rs1506 and rs12421026 (P = 5.48×10⁻¹⁰, 7.93×10⁻¹² and 6.28×10⁻²³ for the three respective groups). The results remained significant after correction for multiple comparisons by permutations. The associated haplotyes found in a previous study were also successfully replicated in this study.

Conclusions/Significance

PAX6 haplotypes are associated with susceptibility to the development of high myopia in Chinese. The PAX6 locus plays a role in high myopia.

Candidate gene association studies

Candidate gene association studies aim to establish or characterise association between the genetic -variation occurring within a specific gene or locus and a phenotype. If the phenotype is quantitative, then the effect size is often measured as the difference between the genotype specific means or a per allele effect. When the phenotype is binary and the disease is either present or absent, the effect is summarised as a genotype specific risk or relative risk. This chapter focuses on methodology employed when a single or small number of genetic loci are being investigated for an association with a specific phenotype.

Common variants in FLNB/CRTAP, not ARHGEF3 at 3p, are associated with osteoporosis in southern Chinese women

SUMMARY

We performed an association study of five candidate genes within chromosome 3p14-25 in 1,080 Chinese female subjects. Polymorphisms in FLNB/CRTAP are associated with bone mineral density (BMD) in Chinese.

INTRODUCTION

Chromosomal region 3p14-25 has shown strong evidence of linkage to BMD in genome-wide linkage scans. The variants responsible for this linkage signal, nonetheless, remain obscure.

METHODS

Thirty SNPs in five positional and functional candidate genes within 3p14-25 (PPARG, CRTAP, TDGF1, PTHR1, and FLNB) and rs7646054 in the ARHGEF3 gene were genotyped in a case-control cohort of 1,080 Chinese females. Allelic and haplotypic association were tested using logistic regression analysis implemented in PLINK software. Potential transcription factor binding sites were predicted with MatInspector.

RESULTS

Multiple SNPs and haplotypes in FLNB were significantly associated with BMDs, with the strongest association between lumbar spine BMD and rs9828717 (p = 0.005). SNP rs7623768 and the haplotype G-C of rs4076086-rs7623768 in CRTAP were associated with femoral neck BMD (p = 0.009 and p = 0.003, respectively). PTHR1 showed haplotypic associations with lumbar spine and femoral neck BMD (p = 0.02 and p = 0.044, respectively). Nevertheless, the association between rs7646054 in ARHGEF3 and BMD observed in Caucasians was not replicated in our samples. Comparative genomics analysis indicated that rs9828717 is located within a highly conserved region. The minor T allele at rs9828717 may lead to loss of binding site for nuclear factor of activated T cells which binds and triggers the transcriptional program of osteoblasts.

CONCLUSIONS

Our data suggest that variants in FLNB and CRTAP at 3p are involved in BMD regulation in southern Chinese.

A data-adaptive sum test for disease association with multiple common or rare variants

Since associations between complex diseases and common variants are typically weak, and approaches to genotyping rare variants (e.g. by next-generation resequencing) multiply, there is an urgent demand to develop powerful association tests that are able to detect disease associations with both common and rare variants. In this article we present such a test. It is based on data-adaptive modifications to a so-called Sum test originally proposed for common variants, which aims to strike a balance between utilizing information on multiple markers in linkage disequilibrium and reducing the cost of large degrees of freedom or of multiple testing adjustment. When applied to multiple common or rare variants in a candidate region, the proposed test is easy to use with 1 degree of freedom and without the need for multiple testing adjustment. We show that the proposed test has high power across a wide range of scenarios with either common or rare variants, or both. In particular, in some situations the proposed test performs better than several commonly used methods.

Statistical tests of genetic association in the presence of gene-gene and gene-environment interactions

BACKGROUND

While its importance is well recognized, it remains challenging to test genetic association in the presence of gene-gene (or gene-environment) interactions. A major technical difficulty lies in the fact that a general model of gene-gene interactions calls for the use of often a large number of parameters, leading to possibly reduced statistical power. An emerging theme of some recent work is to reduce the number of such parameters through dimension reduction. Wang et al. [2009] proposed such an approach based on the partial least squares (PLS) for dimension reduction. They compared their method with several others using simulated data, establishing that their PLS test performed best. Unfortunately, Wang et al. did not include in their evaluations several powerful tests just recently discovered for analyzing multiple SNPs in a candidate gene or region.

METHODS

In this paper, we first extend these tests to the current context to detect gene-gene interactions in the presence of nuisance parameters, then compare these tests with the PLS test using the simulated data of Wang et al. [2009].

RESULTS

It is confirmed that some other tests can be more powerful than the PLS test, though there is no uniform winner. Some interesting, albeit not new, observations are also made: some of the new tests are more robust to the large number of parameters in a model and may thus perform well; on the other hand, even for a purely epistatic genetic model, some of the tests applied to a logistic main-effects model without any interaction terms may be superior to that based on a full model that explicitly accounts for gene-gene interactions.

CONCLUSION

The proposed statistical tests are potentially useful in practice.