Genome-wide association mapping within a local Arabidopsis thaliana population more fully reveals the genetic architecture for defensive metabolite diversity.

Genome-Wide Association Studies Go Green: Novel and Cost-Effective Opportunities for Identifying Genetic Associations

Genome-Wide Association Studies: Does Only Size Matter?

Hybrid vigour, or heterosis, has been of tremendous importance in agriculture for the improvement of both crops and livestock. Notwithstanding large efforts to study the phenomenon of heterosis in the last decades, the identification of common molecular mechanisms underlying hybrid vigour remain rare. Here, we conducted a systematic survey of the degree of heterosis in Arabidopsis thaliana hybrids. For this purpose, two overlapping Arabidopsis hybrid populations were generated by crossing a large collection of naturally occurring accessions to two common reference lines. In these Arabidopsis hybrid populations the range of heterosis for several developmental and yield related traits was examined, and the relationship between them was studied. The traits under study were projected leaf area at 17 days after sowing, flowering time, height of the main inflorescence, number of side branches from the main stem or from the rosette base, total seed yield, seed weight, seed size and the estimated number of seeds per plant. Predominantly positive heterosis was observed for leaf area and height of the main inflorescence, whereas mainly negative heterosis was observed for rosette branching. For the other traits both positive and negative heterosis was observed in roughly equal amounts. For flowering time and seed size only low levels of heterosis were detected. In general the observed heterosis levels were highly trait specific. Furthermore, no correlation was observed between heterosis levels and the genetic distance between the parental lines. Since all selected lines were a part of the Arabidopsis genome wide association (GWA) mapping panel, a genetic mapping approach was applied to identify possible regions harbouring genetic factors causal for heterosis, with separate calculations for additive and dominance effects. Our study showed that the genetic mechanisms underlying heterosis were highly trait specific in our hybrid populations and greatly depended on the genetic background, confirming the elusive character of heterosis.

Systematic review of genome-wide association studies of abdominal aortic aneurysm

The two main hormonal events of a woman's life, menarche and menopause, have a paramount impact on the duration of exposure to estrogen. Reproductive aging phenotypes, including age at menarche (AM) and age at natural menopause (ANM) have been consistently associated with breast cancer risk. Despite an estimated strong genetic component, genome-wide association studies (GWAS) for AM and ANM found that common variants identified to date account for only 7.4% for SNPs related to AM and 2.5-4.1% for ANM. As most previous GWAS on AM and ANM were conducted in women of European ancestry (EA), studies examining genetic components of reproductive aging in African-American (AA) women are needed. We hypothesize that although the index GWAS variants discovered in EA women may differ from those in AA women, rare and low-frequency causal variants may reside in the same genetic regions. A candidate analysis of previously identified GWAS variants and genes in association with AM, ANM was conducted in the African American Breast Cancer Epidemiology and Risk (AMBER) Consortium. All SNPs within a 500kb window of previously discovered GWAS SNPs for AM and ANM were extracted from the Illumina Human Exome Beadchip v1.1, leading to 1,505 candidate SNPs from 125 genes for AM and 1,198 candidate SNPs from 35 genes for ANM in a total of 7,886 AA subjects. Single SNP association tests were run in PLINK using linear regressions for the continuous trend test for AM/ANM and logistic regression for the extreme AM phenotype (<11 v. >=≥15 years). The SKAT-O test for the gene-based analyses was performed using the SKAT R package to aggregate variants with an MAF upper bound of 5%. The top variants related to AM were two SNPs, rs314277 (β=0.11, MAF= 0.45, p=6.24E-05) and rs4742314 (β= -0.11, MAF= 0.39, p=6.44E-05), located in LIN28B and KDM4C respectively. rs974828 (RORA, MAF= 0.23, OR=0.71, p=0.0003) and rs314277 (p=0.0007) were found to be the top variants in association with the extreme AM phenotype. For ANM, rs16991615, located in MCM8, was the most significant variant associated with increased ANM ((β=2.06, MAF= 0.01, p=0.0005). rs314277 (LIN28B) has been previously associated with AM, and rs16991615 (MCM8) had also been related to ANM in previous GWAS in EAs. In gene-based analysis for AM, SLC38A3 (p=0.0007) and WDR6 (p= 0.003) were nominally significant; and EPS8L1 (p= 0.005) and RBM6 (p= 0.01) were associated with the AM phenotype. For ANM, RBMS2 (p= 0.006) was nominally significant in gene-based analysis. This is to date the largest study in AA women for reproductive life events to interrogate rare and low-frequency variants, which are beyond the spectrum of common variants in previous GWAS. Although the overall replication success rate is low, our analyses identified several rare and low-frequency variants in regions from previous GWAS. Our data contributed to the literature on genetic variation for reproductive aging in AA women. Citation Format: Marie V. Coignet, Qianqian Zhu, David G. Cox, Kathryn Lunetta, Elisa V. Bandera, Christopher Haiman, Andrew Olshan, Julie Palmer, Christine Ambrosone, Song Yao. Single variant and gene-based replication analysis of reproductive aging in African American women in the AMBER Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 226.

Background Gliomas, the most common malignant primary brain tumors in adults, typically have a poor prognosis irrespective of medical care. Previous large genome-wide association studies (GWAS) have identified 27 single-nucleotide variants (SNVs) that are significantly associated with glioma. However, most of the GWAS are conducted by case-control study designs, it is therefore prone to bias when rapidly lethal cases don’t have chance to be included in the study. This study aims to replicate the previous GWAS findings using prospective study design. Material and Methods We conducted a nested case-control study within the European Prospective Investigation into Cancer (EPIC) cohort from 7 European countries. GSA-MD Infinium global screening array was used for genotyping. Some subjects were genotyped by other platforms previously. In total, 468 glioma patients and 481 controls were included. The genotypes of 27 SNVs were extracted and for ungenotyped SNVs, datasets were imputed using SHAPEIT v4.1.3 and IMPUTE5 v1.1.5 based on the Haplotype Reference Consortium (Release 1.1) reference panel. Conditional logistic regression model was used to investigate the additive effect of SNVs on the risk of glioma. Results 21 SNVs showed a consistent direction of effect with previous studies, whereas 6 SNVs did not (ORs between 0.72-0.99 and not significant). After adjusting for multiple testing, two SNVs, rs10069690 (TERT), and rs75061358 (near EGFR) were significantly associated with glioma risk. We observed that prominent OR (2.23, 95%CI=1.49-3.33) of rs75061358 in our study compared to the result from previous GWAS, which implied rs75061358 might be not only a risk factor but also affect survival. Different risk direction was observed for rs77633900 in ETFA gene (OR=0.72, 95%CI=0.51-1.01). Conclusion Our findings further confirmed the genetic role on the etiology of glioma in the European population. The potential biases from the previous GWAS are required to be elucidated.

Aims/hypothesisLow birthweight infants are at increased risk not only of mortality, but also of type 2 diabetes mellitus and CVD in later life. At the opposite end of the spectrum, high birthweight infants have increased risk of birth complications, such as shoulder dystocia, neonatal hypoglycaemia and obesity, and similarly increased risk of type 2 diabetes mellitus and CVD. However, previous genome-wide association studies (GWAS) of birthweight in the UK Biobank have primarily focused on individuals within the ‘normal’ range and have excluded individuals with high and low birthweight (<2.5 kg or >4.5 kg). The aim of this study was to investigate genetic variation associated within the tail ends of the birthweight distribution, to: (1) see whether the genetic factors operating in these regions were different from those that explained variation in birthweight within the normal range; (2) explore the genetic correlation between extremes of birthweight and cardiometabolic disease; and (3) investigate whether analysing the full distribution of birthweight values, including the extremes, improved the ability to detect genuine loci in GWAS.MethodsWe performed case–control GWAS analysis of low (<2.5 kg) and high (>4.5 kg) birthweight in the UK Biobank using REGENIE software (Nlow=20,947; Nhigh=12,715; Ncontrols=207,506) and conducted three continuous GWAS of birthweight, one including the full range of birthweights, one involving a truncated GWAS including only individuals with birthweights between 2.5 and 4.5 kg and a third GWAS that winsorised birthweight values <2.5 kg and >4.5 kg. Additionally, we performed bivariate linkage disequilibrium (LD) score regression to estimate the genetic correlation between low/normal/high birthweight and cardiometabolic traits.ResultsBivariate LD score regression analyses suggested that high birthweight had a mostly similar genetic aetiology to birthweight within the normal range (genetic correlation coefficient [rG]=0.91, 95% CI 0.83, 0.99), whereas there was more evidence for a separate set of genes underlying low birthweight (rG=−0.74, 95% CI 0.66, 0.82). Low birthweight was also significantly positively genetically correlated with most cardiometabolic traits and diseases we examined, whereas high birthweight was mostly positively genetically correlated with adiposity and anthropometric-related traits. The winsorisation strategy performed best in terms of locus detection, with the number of independent genome-wide significant associations (p<5×10−8) increasing from 120 genetic variants at 94 loci in the truncated GWAS to 270 genetic variants at 178 loci, including 27 variants at 25 loci that had not been identified in previous birthweight GWAS. This included a novel low-frequency missense variant in the ABCC8 gene, a gene known to be involved in congenital hyperinsulinism, neonatal diabetes mellitus and MODY, that was estimated to be responsible for a 170 g increase in birthweight amongst carriers.Conclusions/interpretationOur results underscore the importance of genetic factors in the genesis of the phenotypic correlation between birthweight and cardiometabolic traits and diseases.Graphical

1 Background: Currently genome-wide association studies (GWAS) have identified over 100 prostate cancer (PrCa) susceptibility loci, capturing 33% of the PrCa familial relative risk (FRR) in Europeans. To identify further susceptibility variants, we conducted a PrCa GWAS, larger than previous studies, comprising ~49,000 cases and ~29,000 controls among individuals of European and Asian descent using the OncoArray, a platform consisting of a 260K GWAS backbone and 310K custom content selected from previous GWAS and fine-mapping studies of multiple cancers ( http://epi.grants.cancer.gov/oncoarray/ ). Methods: Genotypes from the OncoArray were used to impute genotypes from ~70M variants using the October 2014 release of the 1000 genomes project as a reference, and then combined with several previous PrCa GWAS of European ancestry: UK stage 1 (1,906 cases/1,934 controls) and stage 2 (3,888 cases/3,956 controls); CaPS 1 (498 cases/502 controls) and CaPS 2 (1,483 cases/519 controls); BPC3 (2,137 cases/3,101 controls); NCI PEGASUS (4,622 cases/2,954 controls); and iCOGS (21,209 cases/ 20,440 controls). Risk analyses for overall PrCa risk, aggressive PrCa (several definitions defined by PrCa clinical characteristics), and Gleason score were performed. Logistic and linear regression summary statistics were meta-analysed using an inverse variance fixed effect approach. Results: We identified novel loci significantly associated ( P &lt; 5.0x10-8) with overall PrCa (N = 65). Our novel findings are comprised of several missense variants, including a SNP in the ATM gene - a key member of the DNA repair pathway. When combined multiplicatively, the 65 novel PrCa loci identified here increases the captured heritability of PrCa, explaining 38.5% of the FRR when combining novel and previously identified PrCa loci. Conclusions: In risk stratification, men in the top 1% of the genetic risk score group have a relative risk of 5.6 fold for developing PrCa compared with the median risk group. These results will improve the utility of genetic risk scores for targeted screening and prevention for prostate cancer.

MP70-09 IDENTIFICATION OF NINE NEW SUSCEPTIBILITY LOCI FOR PROSTATE CANCER IN THE JAPANESE POPULATION

Embracing diversity: a genetic marker dataset with increased marker density facilitates association studies in maize

The Arabidopsis HapMap population is the center point of this collaboration, used by scientists in eight chair groups to study responses to eleven different individual stresses, and some combinations of these stresses. The main objectives that I address in this thesis are: (1) the development of a video-tracking platform to screen plants for resistance to F. occidentalis, (2) the identification and characterization of novel thrips-resistance genes and mechanisms in the Arabidopsis HapMap population.

Association mapping study conducted in a population of 3490 elite barley breeding lines from ten barley breeding programs of the USA identified 12 QTLs for resistance/susceptibility to net form of net blotch. Breeding resistant varieties is the best management strategy for net form of net blotch (NFNB) in barley (Hordeum vulgare L.) caused by Pyrenophora teres f. teres (Ptt). Several resistance QTL have been previously identified in barley via linkage mapping and genome-wide association studies (GWAS). A GWAS conducted in a collection of advanced breeding lines (n = 3490) representing elite germplasm from ten barley breeding programs of the USA identified 42 unique marker-trait associations (MTA) for NFNB resistance. The lines were genotyped with 3072 SNP markers and phenotyped with four Ptt isolates in controlled environment. The lines were used to construct 13 different GWAS panels. Efficient mixed model association method with principal components and kinship was used for GWAS. Significance threshold for MTA was set at a false discovery rate of 0.05. Two, eight, six, one and 25 MTA were identified in chromosomes 1H, 3H, 4H, 5H and 6H, respectively. Based on genetic positions and linkage disequilibrium, these MTA's correspond to two, three, two, one and four QTLs in chromosome 1H, 3H, 4H, 5H and 6H, respectively. A comparison with previous linkage and GWAS studies revealed several previously identified and novel QTLs. Moreover, different genomic regions were found to be responsible for NFNB resistance in two-row versus six-row germplasm. The germplasm-specific SNP markers with additive effects and allelic distribution is reported to facilitate breeders in selection of markers for MAS to introgress novel net blotch resistance.

BackgroundGermline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking behaviors and DNA repair genes, but further work is required to identify susceptibility variants.MethodsTo identify LC susceptibility loci, a family history-based genome-wide association by proxy (GWAx) of LC (48 843 European proxy LC patients, 195 387 controls) was combined with a previous LC GWAS (29 266 patients, 56 450 controls) by meta-analysis. Colocalization was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic risk scores (PRS) were tested within an independent validation cohort (1 666 LC patients vs 6 664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumor resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided.ResultsThe GWAx–GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1), and smoking propensity genes (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as subgenome-wide significant variants related to expression quantitative trait loci and/or smoking propensity, assisted in LC genetic risk prediction (odds ratio = 1.37, 95% confidence interval = 1.29 to 1.45; P < .001). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumors.ConclusionsThis study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

Impact on venous thrombosis risk of newly discovered gene variants associated with FVIII and VWF plasma levels

In Arabidopsis, a variety of mapping populations have been used for the detection of quantitative trait loci (QTLs) responsible for natural variation. In this study, we present an overview of the advantages and disadvantages of the different types of populations used. To do this, we compare the results of both experimental and natural populations for the commonly analysed trait flowering time. It is expected that genome wide association (GWA) mapping will be an increasingly important tool for QTL mapping because of the high allelic richness and mapping resolution in natural populations. In Arabidopsis, GWA mapping becomes ever more facilitated by the increasing availability of re-sequenced genomes of many accessions. However, specifically designed mapping populations such as recombinant inbred lines and near isogenic lines will remain important. The high QTL detection power of such experimental populations can identify spurious GWA associations, and their unique genomic structure is superior for investigating the role of low-frequency alleles. Future QTL studies will therefore benefit from a combined approach of GWA and classical linkage analysis.