A new efficient method to detect genetic interactions for lung cancer GWAS

BACKGROUND

Genome-wide association studies (GWAS) have proven successful in predicting genetic risk of disease using single-locus models; however, identifying single nucleotide polymorphism (SNP) interactions at the genome-wide scale is limited due to computational and statistical challenges. We addressed the computational burden encountered when detecting SNP interactions for survival analysis, such as age of disease-onset. To confront this problem, we developed a novel algorithm, called the Efficient Survival Multifactor Dimensionality Reduction (ES-MDR) method, which used Martingale Residuals as the outcome parameter to estimate survival outcomes, and implemented the Quantitative Multifactor Dimensionality Reduction method to identify significant interactions associated with age of disease-onset.

METHODS

To demonstrate efficacy, we evaluated this method on two simulation data sets to estimate the type I error rate and power. Simulations showed that ES-MDR identified interactions using less computational workload and allowed for adjustment of covariates. We applied ES-MDR on the OncoArray-TRICL Consortium data with 14,935 cases and 12,787 controls for lung cancer (SNPs = 108,254) to search over all two-way interactions to identify genetic interactions associated with lung cancer age-of-onset. We tested the best model in an independent data set from the OncoArray-TRICL data.

RESULTS

Our experiment on the OncoArray-TRICL data identified many one-way and two-way models with a single-base deletion in the noncoding region of BRCA1 (HR 1.24, P = 3.15 × 10-15), as the top marker to predict age of lung cancer onset.

CONCLUSIONS

From the results of our extensive simulations and analysis of a large GWAS study, we demonstrated that our method is an efficient algorithm that identified genetic interactions to include in our models to predict survival outcomes.

Genetic architecture of cardiometabolic risks in people living with HIV

BACKGROUND

Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown.

METHODS

We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH.

RESULTS

We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI.

CONCLUSIONS

Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.

Genome-wide association studies and whole-genome prediction reveal the genetic architecture of KRN in maize

BACKGROUND

Kernel row number (KRN) is an important trait for the domestication and improvement of maize. Exploring the genetic basis of KRN has great research significance and can provide valuable information for molecular assisted selection.

RESULTS

In this study, one single-locus method (MLM) and six multilocus methods (mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB and ISIS EM-BLASSO) of genome-wide association studies (GWASs) were used to identify significant quantitative trait nucleotides (QTNs) for KRN in an association panel including 639 maize inbred lines that were genotyped by the MaizeSNP50 BeadChip. In three phenotyping environments and with best linear unbiased prediction (BLUP) values, the seven GWAS methods revealed different numbers of KRN-associated QTNs, ranging from 11 to 177. Based on these results, seven important regions for KRN located on chromosomes 1, 2, 3, 5, 9, and 10 were identified by at least three methods and in at least two environments. Moreover, 49 genes from the seven regions were expressed in different maize tissues. Among the 49 genes, ARF29 (Zm00001d026540, encoding auxin response factor 29) and CKO4 (Zm00001d043293, encoding cytokinin oxidase protein) were significantly related to KRN, based on expression analysis and candidate gene association mapping. Whole-genome prediction (WGP) of KRN was also performed, and we found that the KRN-associated tagSNPs achieved a high prediction accuracy. The best strategy was to integrate all of the KRN-associated tagSNPs identified by all GWAS models.

CONCLUSIONS

These results aid in our understanding of the genetic architecture of KRN and provide useful information for genomic selection for KRN in maize breeding.

The Candidate Genes Underlying a Stably Expressed QTL for Low Temperature Germinability in Rice (Oryza sativa L.)

BACKGROUND

Direct seeding is an efficient cultivation technique in rice. However, poor low temperature germinability (LTG) of modern rice cultivars limits its application. Identifying the genes associated with LTG and performing molecular breeding is the fundamental way to address this issue. However, few LTG QTLs have been fine mapped and cloned so far.

RESULTS

In the present study, the LTG evaluation of 375 rice accessions selected from the Rice Diversity Panel 2 showed that there were large LTG variations within the population, and the LTG of Indica group was significantly higher than that of Japonica and Aus groups (p < 0.01). In total, eleven QTLs for LTG were identified through genome-wide association study (GWAS). Among them, qLTG_sRDP2-3/qLTG_JAP-3, qLTG_AUS-3 and qLTG_sRDP2-12 are first reported in the present study. The QTL on chromosome 10, qLTG_sRDP2-10a had the largest contribution to LTG variations in 375 rice accessions, and was further validated using single segment substitution line (SSSL). The presence of qLTG_sRDP2-10a could result in 59.8% increase in LTG under 15 °C low temperature. The expression analysis of the genes within qLTG_sRDP2-10a region indicated that LOC_Os10g22520 and LOC_Os10g22484 exhibited differential expression between the high and low LTG lines. Further sequence comparisons revealed that there were insertion and deletion sequence differences in the promoter and intron region of LOC_Os10g22520, and an about 6 kb variation at the 3' end of LOC_Os10g22484 between the high and low LTG lines, suggesting that the sequence variations of the two genes could be the cause for their differential expression in high and low LTG lines.

CONCLUSION

Among the 11 QTLs identified in this study, qLTG_sRDP2-10a could also be detected in other three studies using different germplasm under different cold environments. Its large effect and stable expression make qLTG_sRDP2-10a particularly valuable in rice breeding. The two genes, LOC_Os10g22484 and LOC_Os10g22520, were considered as the candidate genes underlying qLTG_sRDP2-10a. Our results suggest that integrating GWAS and SSSL can facilitate identification of QTL for complex traits in rice. The identification of qLTG_sRDP2-10a and its candidate genes provide a promising source for gene cloning of LTG and molecular breeding for LTG in rice.

The association of genetic polymorphisms with nonalcoholic fatty liver disease in a longitudinal study

Background

Several genetic variants are known to be associated with nonalcoholic fatty liver disease (NAFLD). We aimed to evaluate the longitudinal associations between genetic variants and NAFLD.

Methods

We performed a genome-wide association study (GWAS) in Korean individuals who underwent repeated health check-ups. NAFLD was defined by ultrasonography and exclusion of secondary causes.

Results

The subjects had a median age of 50.0 years, and 54.8% were male. The median follow-up duration was 39 months. Among the 3905 subjects without NAFLD at baseline, 874 (22.4%) subjects developed NAFLD, and among the 1818 subjects with NAFLD at baseline, NAFLD regressed in 336 (18.5%) subjects during the follow-up period. After adjusting for age, sex and body mass index, no single-nucleotide polymorphism (SNP) passed Bonferroni correction for genome-wide significance in the development or regression of NAFLD. Among the SNPs that passed the genome-wide suggestiveness threshold (p = 1E-04) in the discovery set in the GWAS, only 1 SNP (rs4906353) showed an association with the development of NAFLD, with marginal significance in the validation set (p-value, discovery set = 9.68E-5 and validation set = 0.00531).

Conclusions

This exploratory study suggests that longitudinal changes in NAFLD are not associated with genetic variants in the Korean population. These findings provide new insight into genetic mechanisms in the pathogenesis of NAFLD.

A combination of genome-wide association study and transcriptome analysis in leaf epidermis identifies candidate genes involved in cuticular wax biosynthesis in Brassica napus

BACKGROUND

Brassica napus L. is one of the most important oil crops in the world. However, climate-change-induced environmental stresses negatively impact on its yield and quality. Cuticular waxes are known to protect plants from various abiotic/biotic stresses. Dissecting the genetic and biochemical basis underlying cuticular waxes is important to breed cultivars with improved stress tolerance.

RESULTS

Here a genome-wide association study (GWAS) of 192 B. napus cultivars and inbred lines was used to identify single-nucleotide polymorphisms (SNPs) associated with leaf waxes. A total of 202 SNPs was found to be significantly associated with 31 wax traits including total wax coverage and the amounts of wax classes and wax compounds. Next, epidermal peels from leaves of both high-wax load (HW) and low-wax load (LW) lines were isolated and used to analyze transcript profiles of all GWAS-identified genes. Consequently, 147 SNPs were revealed to have differential expressions between HW and LW lines, among which 344 SNP corresponding genes exhibited up-regulated while 448 exhibited down-regulated expressions in LW when compared to those in HW. According to the gene annotation information, some differentially expressed genes were classified into plant acyl lipid metabolism, including fatty acid-related pathways, wax and cutin biosynthesis pathway and wax secretion. Some genes involved in cell wall formation and stress responses have also been identified.

CONCLUSIONS

Combination of GWAS with transcriptomic analysis revealed a number of directly or indirectly wax-related genes and their associated SNPs. These results could provide clues for further validation of SNPs for marker-assisted breeding and provide new insights into the genetic control of wax biosynthesis and improving stress tolerance of B. napus.

Novel genetic variants of PIP5K1C and MVB12B of the endosome-related pathway predict cutaneous melanoma-specific survival

Endosomes regulate cell polarity, adhesion, signaling, immunity, and tumor progression, which may influence cancer outcomes. Here we evaluated associations between 36,068 genetic variants of 228 endosome-related pathway genes and cutaneous melanoma disease-specific survival (CMSS) using genotyping data from two previously published genome-wide association studies. The discovery dataset included 858 CM patients with 95 deaths from The University of Texas MD Anderson Cancer Center, and the replication dataset included 409 CM patients with 48 deaths from the Nurses' Health Study (NHS) and the Health Professionals Follow-up Study (HPFS). In multivariate Cox proportional hazards regression analysis, we found that two novel SNPs (PIP5K1C rs11666894 A>C and MVB12B rs12376285 C>T) predicted CMSS, with adjusted hazards ratios of 1.47 (95% confidence interval = 1.15-1.89 and P = 0.002) and 1.73 (1.30-2.31 and 0.0002), respectively. Combined analysis of risk genotypes of these two SNPs revealed a dose-dependent decrease in CMSS associated with an increased number of risk genotypes (P _trend = 0.0002). Subsequent expression quantitative trait loci (eQTL) analysis revealed that PIP5K1C rs11666894 was associated with mRNA expression levels in lymphoblastoid cell lines from 373 European descendants (P<0.0001) and that MVB12B rs12376285 was associated with mRNA expression levels in cultured fibroblasts from 605 European-Americans (P<0.0001). Our findings suggest that novel genetic variants of PIP5K1C and MVB12B in the endosome-related pathway genes may be promising prognostic biomarkers for CMSS, but these results need to be validated in future larger studies.

Variation in the response to exercise stimulation in Drosophila: marathon runner versus sprinter genotypes

Animals' behaviors vary in response to their environment, both biotic and abiotic. These behavioral responses have significant impacts on animal survival and fitness, and thus, many behavioral responses are at least partially under genetic control. In Drosophila, for example, genes impacting aggression, courtship behavior, circadian rhythms and sleep have been identified. Animal activity also is influenced strongly by genetics. My lab previously has used the Drosophila melanogaster Genetics Reference Panel (DGRP) to investigate activity levels and identified over 100 genes linked to activity. Here, I re-examined these data to determine whether Drosophila strains differ in their response to rotational exercise stimulation, not simply in the amount of activity, but in activity patterns and timing of activity. Specifically, I asked whether there are fly strains exhibiting either a 'marathoner' pattern of activity, i.e. remaining active throughout the 2 h exercise period, or a 'sprinter' pattern, i.e. carrying out most of the activity early in the exercise period. The DGRP strains examined differ significantly in how much activity is carried out at the beginning of the exercise period, and this pattern is influenced by both sex and genotype. Interestingly, there was no clear link between the activity response pattern and lifespan of the animals. Using genome-wide association studies (GWAS), I identified 10 high confidence candidate genes that control the degree to which Drosophila exercise behaviors fit a marathoner or sprinter activity pattern. This finding suggests that, similar to other aspects of locomotor behavior, the timing of activity patterns in response to exercise stimulation is under genetic control.

Integrative, genome-wide association study identifies chemicals associated with common women's malignancies

BACKGROUND

Breast cancer, cervical cancer, and ovarian cancer are three of the most commonly diagnosed malignancies in women, and more cancer prevention research is urgently needed.

METHODS

Summary data of a large genome-wide association study of female cancers were derived from the UK biobank. We performed a transcriptome-wide association study and a gene set enrichment analysis to identify correlations between chemical exposure and aberrant expression, repression, or mutation of genes related to cancer using the Comparative Toxicogenomics Database.

RESULTS

We identified five chemicals (NSC668394, glafenine, methylnitronitrosoguanidine, fenofibrate, and methylparaben) that were associated with the incidence of both breast cancer and cervical cancer.

CONCLUSION

Using a transcriptome-wide association study and gene set enrichment analysis we identified environmental chemicals that are associated with an increased risk of breast cancer, cervical cancer, and ovarian cancer.

Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease

BACKGROUND

Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration.

METHODS

A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD.

RESULTS

We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10-3) and HSPA2 (FDR p = 0.245).

CONCLUSIONS

Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach.

Environmental and genetic determinants of amphicarpy in Pisum fulvum, a wild relative of domesticated pea

Pisum fulvum is an annual legume native to Syria, Lebanon, Israel and Jordan. In certain locations, P. fulvum individuals were documented to display a reproductive dimorphism - amphicarpy, with both above and below ground flowers and pods. Herein we aimed to study the possible role of soil texture on amphicarpy in P. fulvum, to investigate the possible bio-climatic associations of P. fulvum amphicarpy and to identify genetic markers associated with this phenotype. A set of 127 germplasm accessions sampled across the Israeli distribution range of the species was phenotyped in two common garden nurseries. Land use and bioclimatic data were used to delineate the eco-geographic clustering of accession's sampling sites. Single nucleotide polymorphism (SNP) markers were employed in genome-wide association study to identify associated loci. Amphicarpy was subject to strong experimental site x genotype interaction with higher phenotypic expression in fine textured soil relative to sandy loam. Amphicarpy was more prevalent among accessions sampled in eastern Judea and Samaria and was weakly associated with early phenology and relatively modest above ground biomass production. Twelve SNP markers were significantly associated with amphicarpy, each explaining between 8 and 12 % of the phenotypic variation. In P. fulvum amphicarpy seems to be a polygenetic trait controlled by an array of genes that is likely to be affected by environmental stimuli. The probable selective advantage of the association between amphicarpy and early flowering is in line with its relative prevalence in drought prone territories subject to heavy grazing.

Multiple independent mechanisms link gene polymorphisms in the region of ZEB2 with risk of coronary artery disease

BACKGROUND AND AIMS

Coronary artery disease (CAD) arises from the interaction of genetic and environmental factors. Although genome-wide association studies (GWAS) have identified multiple risk loci and single nucleotide polymorphisms (SNPs) associated with risk of CAD, they are predominantly located in non-coding or intergenic regions and their mechanisms of effect are largely unknown. Accordingly, our objective was to develop a data-driven informatics pipeline to understand complex CAD risk loci, and to apply this to a poorly understood cluster of SNPs in the vicinity of ZEB2.

METHODS

We developed a unique informatics pipeline leveraging a multi-tissue CAD genetics-of-gene-expression dataset, GWAS datasets, and other resources. The pipeline first dissected SNP locations and their linkage disequilibrium relationships, and progressed through analyses of tissue-specific expression quantitative trait loci, and then gene-gene, gene-phenotype, SNP-phenotype relationships. The pipeline concluded by exploring CAD-relevant gene regulatory networks (GRNs).

RESULTS

We identified three independent CAD risk SNPs in close proximity to the ZEB2 coding region (rs6740731, rs17678683 and rs2252641/rs1830321). Our pipeline determined that these SNPs likely act in concert via the atherosclerotic arterial wall and adipose tissues, by governing metabolic and lipid functions. In addition, ZEB2 is the top key driver of a liver-specific GRN that is related to lipid levels, metabolic and anthropometric measures, and CAD severity.

CONCLUSIONS

Using a novel informatics pipeline, we disclosed the multi-faceted mechanisms of action of the ZEB2-associated CAD risk SNPs. This pipeline can serve as a roadmap to dissect complex SNP-gene-tissue-phenotype relationships and to reveal targets for tissue- and gene-specific therapeutic interventions.

Genome-wide association study identifies candidate genes related to oleic acid content in soybean seeds

BACKGROUND

Soybean oil is a complex mixture of five fatty acids (palmitic, stearic, oleic, linoleic, and linolenic). Soybean oil with a high oleic acid content is desirable because this monounsaturated fatty acid improves the oxidative stability of the oil. To investigate the genetic architecture of oleic acid in soybean seeds, 260 soybean germplasms from Northeast China were collected as natural populations. A genome-wide association study (GWAS) was conducted on a panel of 260 germplasm resources.

RESULTS

Phenotypic identification results showed that the oleic acid content varied from 8.2 to 35.0%. A total of 2,311,337 single-nucleotide polymorphism (SNP) markers were obtained. GWAS analysis showed that there were many genes related to oleic acid content with a contribution rate of 7%. The candidate genes Glyma.11G229600.1 on chromosome 11 and Glyma.04G102900.1 on chromosome 4 were detected in a 2-year-long GWAS. The candidate gene Glyma.11G229600.1 showed a positive correlation with the oleic acid content, and the correlation coefficient was 0.980, while Glyma.04G102900.1 showed a negative correlation, with a coefficient of - 0.964.

CONCLUSIONS

Glyma.04G102900.1 on chromosome 4 and Glyma.11G229600.1 on chromosome 11 were detected in both analyses (2018 and 2019). Glyma.04G102900.1 and Glyma.11G229600.1 are new key candidate genes related to oleic acid in soybean seeds. These results will be useful for high-oleic soybean breeding.

Genome-wide association study reveals the genetic basis of fiber quality traits in upland cotton (Gossypium hirsutum L.)

BACKGROUND

Fiber quality is an important economic trait of cotton, and its improvement is a major goal of cotton breeding. To better understand the genetic mechanisms responsible for fiber quality traits, we conducted a genome-wide association study to identify and mine fiber-quality-related quantitative trait loci (QTLs) and genes.

RESULTS

In total, 42 single nucleotide polymorphisms (SNPs) and 31 QTLs were identified as being significantly associated with five fiber quality traits. Twenty-five QTLs were identified in previous studies, and six novel QTLs were firstly identified in this study. In the QTL regions, 822 genes were identified and divided into four clusters based on their expression profiles. We also identified two pleiotropic SNPs. The SNP locus i52359Gb was associated with fiber elongation, strength, length and uniformity, while i11316Gh was associated with fiber strength and length. Moreover, these two SNPs were nonsynonymous and located in genes Gh_D09G2376 and Gh_D06G1908, respectively. RT-qPCR analysis revealed that these two genes were preferentially expressed at one or more stages of cotton fiber development, which was consistent with the RNA-seq data. Thus, Gh_D09G2376 and Gh_D06G1908 may be involved in fiber developmental processes.

CONCLUSIONS

The findings of this study provide insights into the genetic bases of fiber quality traits, and the identified QTLs or genes may be applicable in cotton breeding to improve fiber quality.

Genome-wide association study identifies locus at chromosome 2q32.1 associated with syncope and collapse

Aims

Syncope is a common condition associated with frequent hospitalization or visits to the emergency department. Family aggregation and twin studies have shown that syncope has a heritable component. We investigated whether common genetic variants predispose to syncope and collapse.

Methods and results

We used genome-wide association data on syncope on 408 961 individuals with European ancestry from the UK Biobank study. In a replication study, we used the Integrative Psychiatric Research Consortium (iPSYCH) cohort (n = 86 189), to investigate the risk of incident syncope stratified by genotype carrier status. We report on a genome-wide significant locus located on chromosome 2q32.1 [odds ratio = 1.13, 95% confidence interval (CI) 1.10–1.17, P = 5.8 × 10⁻¹⁵], with lead single nucleotide polymorphism rs12465214 in proximity to the gene zinc finger protein 804a (ZNF804A). This association was also shown in the iPSYCH cohort, where homozygous carriers of the C allele conferred an increased hazard ratio (1.30, 95% CI 1.15–1.46, P = 1.68 × 10⁻⁵) of incident syncope. Quantitative polymerase chain reaction analysis showed ZNF804A to be expressed most abundantly in brain tissue.

Conclusion

We identified a genome-wide significant locus (rs12465214) associated with syncope and collapse. The association was replicated in an independent cohort. This is the first genome-wide association study to associate a locus with syncope and collapse.

Genome-wide identification of m6A-associated single-nucleotide polymorphisms in Parkinson's disease

N⁶-methyladenosine (m⁶A)-associated single nucleotide polymorphisms (SNPs) play a vital role in several neurological diseases. However, little is known about the relationship between m⁶A modification and Parkinson's disease (PD). We investigated potential functional variants of m⁶A-SNPs from large-scale genome-wide association studies (GWAS) in PD patients. The candidate m⁶A-SNPs were further assessed by expression quantitative trait loci (eQTL) analysis and differential gene expression analysis. We identified 12 m⁶A-SNPs that were significantly associated with PD risk. Further, eQTL and expression analyses identified five of these m⁶A-SNPs (rs75072999 of GAK, rs1378602, rs4924839 and rs8071834 of ALKBH5, and rs1033500 of C6orf10) that were associated with altered gene expression in PD. Our results suggest that m⁶A-SNPs could play a role in PD risk. Future studies are needed to confirm these PD-associated m⁶A-SNPs and elucidate their mechanisms.

Meta-analysis of genome-wide association study identifies FBN2 as a novel locus associated with systemic lupus erythematosus in Thai population

BACKGROUND

Differences in the expression of variants across ethnic groups in the systemic lupus erythematosus (SLE) patients have been well documented. However, the genetic architecture in the Thai population has not been thoroughly examined. In this study, we carried out genome-wide association study (GWAS) in the Thai population.

METHODS

Two GWAS cohorts were independently collected and genotyped: discovery dataset (487 SLE cases and 1606 healthy controls) and replication dataset (405 SLE cases and 1590 unrelated disease controls). Data were imputed to the density of the 1000 Genomes Project Phase 3. Association studies were performed based on different genetic models, and pathway enrichment analysis was further examined. In addition, the performance of disease risk estimation for individuals in Thai GWAS was assessed based on the polygenic risk score (PRS) model trained by other Asian populations.

RESULTS

Previous findings on SLE susceptible alleles were well replicated in the two GWAS. The SNPs on HLA class II (rs9270970, A>G, OR = 1.82, p value = 3.61E-26), STAT4 (rs7582694, C>G, OR = 1.57, p value = 8.21E-16), GTF2I (rs73366469, A>G, OR = 1.73, p value = 2.42E-11), and FAM167A-BLK allele (rs13277113, A>G, OR = 0.68, p value = 1.58E-09) were significantly associated with SLE in Thai population. Meta-analysis of the two GWAS identified a novel locus at the FBN2 that was specifically associated with SLE in the Thai population (rs74989671, A>G, OR = 1.54, p value = 1.61E-08). Functional analysis showed that rs74989671 resided in a peak of H3K36me3 derived from CD14+ monocytes and H3K4me1 from T lymphocytes. In addition, we showed that the PRS model trained from the Chinese population could be applied in individuals of Thai ancestry, with the area under the receiver-operator curve (AUC) achieving 0.76 for this predictor.

CONCLUSIONS

We demonstrated the genetic architecture of SLE in the Thai population and identified a novel locus associated with SLE. Also, our study suggested a potential use of the PRS model from the Chinese population to estimate the disease risk for individuals of Thai ancestry.

Performances of Adaptive MultiBLUP, Bayesian regressions, and weighted-GBLUP approaches for genomic predictions in Belgian Blue beef cattle

BACKGROUND

Genomic selection has been successfully implemented in many livestock and crop species. The genomic best linear unbiased predictor (GBLUP) approach, assigning equal variance to all SNP effects, is one of the reference methods. When large-effect variants contribute to complex traits, it has been shown that genomic prediction methods that assign a higher variance to subsets of SNP effects can achieve higher prediction accuracy. We herein compared the efficiency of several such approaches, including the Adaptive MultiBLUP (AM-BLUP) that uses local genomic relationship matrices (GRM) to automatically identify and weight genomic regions with large effects, to predict genetic merit in Belgian Blue beef cattle.

RESULTS

We used a population of approximately 10,000 genotyped cows and their phenotypes for 14 traits, mostly related to muscular development and body dimensions. According to the trait, we found that 4 to 25% of the genetic variance could be associated with 2 to 12 genomic regions harbouring large-effect variants. Noteworthy, three previously identified recessive deleterious variants presented heterozygote advantage and were among the most significant SNPs for several traits. The AM-BLUP resulted in increased reliability of genomic predictions compared to GBLUP (+ 2%), but Bayesian methods proved more efficient (+ 3%). Overall, the reliability gains remained thus limited although higher gains were observed for skin thickness, a trait affected by two genomic regions having particularly large effects. Higher accuracies than those from the original AM-BLUP were achieved when applying the Bayesian Sparse Linear Mixed Model to pre-select groups of SNPs with large effects and subsequently use their estimated variance to build a weighted GRM. Finally, the single-step GBLUP performed best and could be further improved (+ 3% prediction accuracy) by using these weighted GRM.

CONCLUSIONS

The AM-BLUP is an attractive method to automatically identify and weight genomic regions with large effects on complex traits. However, the method was less accurate than Bayesian methods. Overall, weighted methods achieved modest accuracy gains compared to GBLUP. Nevertheless, the computational efficiency of the AM-BLUP might be valuable at higher marker density, including with whole-genome sequencing data. Furthermore, weighted GRM are particularly useful to account for large variance loci in the single-step GBLUP.

mrMLM v4.0.2: An R Platform for Multi-locus Genome-wide Association Studies

Previous studies have reported that some important loci are missed in single-locus genome-wide association studies (GWAS), especially because of the large phenotypic error in field experiments. To solve this issue, multi-locus GWAS methods have been recommended. However, only a few software packages for multi-locus GWAS are available. Therefore, we developed an R software named mrMLM v4.0.2. This software integrates mrMLM, FASTmrMLM, FASTmrEMMA, pLARmEB, pKWmEB, and ISIS EM-BLASSO methods developed by our lab. There are four components in mrMLM v4.0.2, including dataset input, parameter setting, software running, and result output. The fread function in data.table is used to quickly read datasets, especially big datasets, and the doParallel package is used to conduct parallel computation using multiple CPUs. In addition, the graphical user interface software mrMLM.GUI v4.0.2, built upon Shiny, is also available. To confirm the correctness of the aforementioned programs, all the methods in mrMLM v4.0.2 and three widely-used methods were used to analyze real and simulated datasets. The results confirm the superior performance of mrMLM v4.0.2 to other methods currently available. False positive rates are effectively controlled, albeit with a less stringent significance threshold. mrMLM v4.0.2 is publicly available at BioCode (https://bigd.big.ac.cn/biocode/tools/BT007077) or R (https://cran.r-project.org/web/packages/mrMLM.GUI/index.html) as an open-source software.

Genome-wide association study of turnip mosaic virus resistance in non-heading Chinese cabbage

A genome-wide association study (GWAS) using 83 diverse non-heading Chinese cabbage (NHCC) accessions identified 42,526 high-quality single nucleotide polymorphism markers associated with turnip mosaic virus (TuMV) resistance. Seventeen associated loci were identified, along with the related genes that were differentially expressed between resistant and susceptible varieties, suggesting that they may be candidate genes for TuMV tolerance. Nine mutant genes of Arabidopsis were selected for inoculation with TuMV-GFP (green fluorescence protein) to further confirm the disease resistance of these genes. Quantitative polymerase chain reaction (qPCR) analysis showed that the virus content in the Arabidopsis mutants with the homologous genes of cell wall-associated proteins, pectin methyl-esterase (PME), transcription factors (TFs), resistance gene (R), VAN3/SFC protein and F-box gene were significantly higher than that in the mutants with the homologous genes of methylation and J protein. Our results provide the basis of further study of the potential function of these candidate TuMV resistance genes and demonstrate that the described diverse NHCC can be efficiently used for GWAS of various quantitative traits. Taken together, the findings of this study will be useful to improve TuMV resistance in NHCC breeding and to discover new genes related to TuMV resistance.

Genome-wide and Mendelian randomisation studies of liver MRI yield insights into the pathogenesis of steatohepatitis

BACKGROUND & AIMS

MRI-based corrected T1 (cT1) is a non-invasive method to grade the severity of steatohepatitis and liver fibrosis. We aimed to identify genetic variants influencing liver cT1 and use genetics to understand mechanisms underlying liver fibroinflammatory disease and its link with other metabolic traits and diseases.

METHODS

First, we performed a genome-wide association study (GWAS) in 14,440 Europeans, with liver cT1 measures, from the UK Biobank. Second, we explored the effects of the cT1 variants on liver blood tests, and a range of metabolic traits and diseases. Third, we used Mendelian randomisation to test the causal effects of 24 predominantly metabolic traits on liver cT1 measures.

RESULTS

We identified 6 independent genetic variants associated with liver cT1 that reached the GWAS significance threshold (p <5×10-8). Four of the variants (rs759359281 in SLC30A10, rs13107325 in SLC39A8, rs58542926 in TM6SF2, rs738409 in PNPLA3) were also associated with elevated aminotransferases and had variable effects on liver fat and other metabolic traits. Insulin resistance, type 2 diabetes, non-alcoholic fatty liver and body mass index were causally associated with elevated cT1, whilst favourable adiposity (instrumented by variants associated with higher adiposity but lower risk of cardiometabolic disease and lower liver fat) was found to be protective.

CONCLUSION

The association between 2 metal ion transporters and cT1 indicates an important new mechanism in steatohepatitis. Future studies are needed to determine whether interventions targeting the identified transporters might prevent liver disease in at-risk individuals.

LAY SUMMARY

We estimated levels of liver inflammation and scarring based on magnetic resonance imaging of 14,440 UK Biobank participants. We performed a genetic study and identified variations in 6 genes associated with levels of liver inflammation and scarring. Participants with variations in 4 of these genes also had higher levels of markers of liver cell injury in blood samples, further validating their role in liver health. Two identified genes are involved in the transport of metal ions in our body. Further investigation of these variations may lead to better detection, assessment, and/or treatment of liver inflammation and scarring.

Deciphering the mode of action and position of genetic variants impacting on egg number in broiler breeders

Background

Aim of the present study was first to identify genetic variants associated with egg number (EN) in female broilers, second to describe the mode of their gene action (additive and/or dominant) and third to provide a list with implicated candidate genes for the trait. A number of 2586 female broilers genotyped with the high density (~ 600 k) SNP array and with records on EN (mean = 132.4 eggs, SD = 29.8 eggs) were used. Data were analyzed with application of additive and dominant multi-locus mixed models.

Results

A number of 7 additive, 4 dominant and 6 additive plus dominant marker-trait significant associations were detected. A total number of 57 positional candidate genes were detected within 50 kb downstream and upstream flanking regions of the 17 significant markers. Functional enrichment analysis pinpointed two genes (BHLHE40 and CRTC1) to be involved in the ‘entrainment of circadian clock by photoperiod’ biological process. Gene prioritization analysis of the positional candidate genes identified 10 top ranked genes (GDF15, BHLHE40, JUND, GDF3, COMP, ITPR1, ELF3, ELL, CRLF1 and IFI30). Seven prioritized genes (GDF15, BHLHE40, JUND, GDF3, COMP, ELF3, CRTC1) have documented functional relevance to reproduction, while two more prioritized genes (ITPR1 and ELL) are reported to be related to egg quality in chickens.

Conclusions

Present results have shown that detailed exploration of phenotype-marker associations can disclose the mode of action of genetic variants and help in identifying causative genes associated with reproductive traits in the species.

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

Background

Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithms to be securely deployed in the cloud because operations on encrypted genomic databases are conducted without revealing any individual genomes. Methods for secure computation have shown significant performance improvements over the last several years. However, it is still challenging to apply them on large biomedical datasets.

Methods

The HE Track of iDash 2018 competition focused on solving an important problem in practical machine learning scenarios, where a data analyst that has trained a regression model (both linear and logistic) with a certain set of features, attempts to find all features in an encrypted database that will improve the quality of the model. Our solution is based on the hybrid framework Chimera that allows for switching between different families of fully homomorphic schemes, namely TFHE and HEAAN.

Results

Our solution is one of the finalist of Track 2 of iDash 2018 competition. Among the submitted solutions, ours is the only bootstrapped approach that can be applied for different sets of parameters without re-encrypting the genomic database, making it practical for real-world applications.

Conclusions

This is the first step towards the more general feature selection problem across large encrypted databases.

Heritability and genome-wide association analyses of fasting plasma glucose in Chinese adult twins

Background

Currently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins.

Results

The final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (r_DZ = 0.20, 95% CI: 0.04–0.36) was much lower than half that of the MZ twin correlation (r_MZ = 0.68, 95% CI: 0.62–0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50–73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38–39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10^− 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10^− 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10^− 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10^− 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as β-alanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified.

Conclusions

The FPG level is highly heritable in the Chinese population, and genetic variants are significantly involved in regulatory domains, functional genes and biological pathways that mediate FPG levels. This study provides important clues for further elucidating the molecular mechanism of glucose homeostasis and discovering new diagnostic biomarkers and therapeutic targets for diabetes.

QTL Mapping and Candidate Gene Analysis for Alkali Tolerance in Japonica Rice at the bud Stage Based on Linkage Mapping and Genome-Wide Association Study

BACKGROUND

Salinity-alkalinity stress is one of the major factors limiting rice production. Damage caused by alkaline salt stress is more severe than that caused by neutral salt stress. Alkali tolerance at the bud stage in rice directly affects seedling survival and final yield when using the direct seeding cultivation model. However, genetic resources (QTLs and genes) for rice breeders to improve alkali tolerance are limited. In this study, we combined linkage mapping and a genome-wide association study (GWAS) to analyze the genetic structure of this trait in japonica rice at the bud stage.

RESULTS

A population of 184 recombinant inbred lines (RILs) was utilized to map quantitative trait loci (QTLs) for the root length under control condition (RL), alkaline stress (ARL) and relative root length (RRL) at the bud stage. A major QTL related to alkali tolerance at the rice bud stage, qAT11, was detected on chromosome 11. Interestingly, a GWAS identified a lead SNP (Chr_21,999,659) in qAT11 that was significantly associated with alkaline tolerance. After filtering by linkage disequilibrium (LD), haplotype analysis, quantitative real-time PCR, we obtained three candidate genes (LOC_Os11g37300, LOC_Os11g37320 and LOC_Os11g37390). In addition, we performed phenotype verification on the CRISPR/Cas9 mutant of LOC_Os11g37390.

CONCLUSION

Based on these results, LOC_Os11g37300, LOC_Os11g37320 and LOC_Os11g37390 were the candidate genes contributing to alkaline tolerance in japonica rice. This study provides resources for breeding aimed at improving rice responses to alkalinity stress.