Phenotypic Characterization of a Major Quantitative Disease Resistance Locus for Partial Resistance to Phytophthora sojae

Major quantitative disease resistance loci (QDRLs) are rare in the Phytophthora sojae (Kaufmann and Gerdemann)–soybean [Glycine max (L). Merr.] pathosystem. A major QDRL on chromosome 18 (QDRL-18) was identified in PI 427105B and PI 427106. QDRL-18 represents a valuable resistance source for breeding programs. Thus, our objectives were to determine its isolate specificity and measure its effect on yield and resistance to both P. sojae and other soybean pathogens. We characterized near isogenic lines (NILs) developed from F7 recombinant inbred lines heterozygous at QDRL-18; NILs represent introgressions from PI 427105B, PI 427106, and susceptible ‘OX20- 8’. The introgressions from PI 427105B and PI 427106 increased resistance to P. sojae by 11 to 20% and 35 to 40%, respectively, based on laboratory and greenhouse assays, and increased yield by 13 to 29% under disease conditions. The resistant introgression from PI 427105B was also effective against seven P. sojae isolates with no isolate specificity detected. Based on quantitative polymerase chain reaction assays, NILs with the susceptible introgression had significantly higher relative levels of P. sojae colonization 48 h after inoculation. No pleiotropic effects for resistance to either soybean cyst nematode or Fusarium graminearum were detected. This information improves soybean breeders’ ability to make informed decisions regarding the deployment of QDRL-18 in their respective breeding programs

Assessment of gene-by-sex interaction effect on bone mineral density

To access publisher's full text version of this article. Please click on the hyperlink in Additional Links field.Sexual dimorphism in various bone phenotypes, including bone mineral density (BMD), is widely observed; however, the extent to which genes explain these sex differences is unclear. To identify variants with different effects by sex, we examined gene-by-sex autosomal interactions genome-wide, and performed expression quantitative trait loci (eQTL) analysis and bioinformatics network analysis. We conducted an autosomal genome-wide meta-analysis of gene-by-sex interaction on lumbar spine (LS) and femoral neck (FN) BMD in 25,353 individuals from 8 cohorts. In a second stage, we followed up the 12 top single-nucleotide polymorphisms (SNPs; p < 1 × 10(-5) ) in an additional set of 24,763 individuals. Gene-by-sex interaction and sex-specific effects were examined in these 12 SNPs. We detected one novel genome-wide significant interaction associated with LS-BMD at the Chr3p26.1-p25.1 locus, near the GRM7 gene (male effect = 0.02 and p = 3.0 × 10(-5) ; female effect = -0.007 and p = 3.3 × 10(-2) ), and 11 suggestive loci associated with either FN- or LS-BMD in discovery cohorts. However, there was no evidence for genome-wide significant (p < 5 × 10(-8) ) gene-by-sex interaction in the joint analysis of discovery and replication cohorts. Despite the large collaborative effort, no genome-wide significant evidence for gene-by-sex interaction was found to influence BMD variation in this screen of autosomal markers. If they exist, gene-by-sex interactions for BMD probably have weak effects, accounting for less than 0.08% of the variation in these traits per implicated SNP. © 2012 American Society for Bone and Mineral Research.Medtronic NIH R01 AG18728 R01HL088119 R01AR046838 U01 HL084756 R01 AR43351 P01-HL45522 R01-MH-078111 R01-MH-083824 Nutrition and Obesity Research Center of Maryland P30DK072488 NIAMS/NIH F32AR059469 Instituto de Salud Carlos III-FIS (Spanish Health Ministry) PI 06/0034 PI08/0183 Canadian Institutes of Health Research (CIHR) NHLBI HHSN268201200036C N01-HC-85239 N01-HC-85079 N01-HC-85086 N01-HC-35129 N01 HC15103 N01 HC-55222 N01-HC-75150 N01-HC-45133 HL080295 HL087652 HL105756 NIA AG-023629 AG-15928 AG-20098 AG-027058 N01AG62101 N01AG62103 N01AG62106 1R01AG032098-01A1 National Center of Advancing Translational Technologies CTSI UL1TR000124 National Institute of Diabetes and Digestive and Kidney Diseases DK063491 EUROSPAN (European Special Populations Research Network) European Commission FP6 STRP grant 018947 LSHG-CT-2006-01947 Netherlands Organisation for Scientific Research Erasmus MC Centre for Medical Systems Biology (CMSB) Netherlands Brain Foundation (HersenStichting Nederland) US National Institute for Arthritis, Musculoskeletal and Skin Diseases National Institute on Aging R01 AR/AG41398 R01 AR050066 R21 AR056405 National Heart, Lung, and Blood Institute's Framingham Heart Study N01-HC-25195 Affymetrix, Inc. N02-HL-6-4278 Canadian Institutes of Health Research from Institute of Aging 165446 Institute of Genetics 179433 Institute of Musculoskeletal health 221765 Intramural Research Program of the NIH, National Institute on Aging National Institutes of Health HHSN268200782096C Hong Kong Research Grant Council HKU 768610M Bone Health Fund of HKU Foundation KC Wong Education Foundation Small Project Funding 201007176237 Matching Grant CRCG Grant Osteoporosis and Endocrine Research Fund Genomics Strategic Research Theme of The University of Hong Kong Netherlands Organisation of Scientific Research NWO Investments 175.010.2005.011 911-03-012 Research Institute for Diseases in the Elderly 014-93-015 Netherlands Genomics Initiative (NGI)/Netherlands Consortium for Healthy Aging (NCHA) 050-060-810 Erasmus Medical Center and Erasmus University, Rotterdam Netherlands Organization for the Health Research and Development (ZonMw) Research Institute for Diseases in the Elderly (RIDE) Ministry of Education, Culture and Science Ministry for Health, Welfare and Sports European Commission (DG XII) Municipality of Rotterdam German Bundesministerium fur Forschung und Technology 01 AK 803 A-H 01 IG 07015

Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects.

Bone mineral density (BMD) assessed by DXA is used to evaluate bone health. In children, total body (TB) measurements are commonly used; in older individuals, BMD at the lumbar spine (LS) and femoral neck (FN) is used to diagnose osteoporosis. To date, genetic variants in more than 60 loci have been identified as associated with BMD. To investigate the genetic determinants of TB-BMD variation along the life course and test for age-specific effects, we performed a meta-analysis of 30 genome-wide association studies (GWASs) of TB-BMD including 66,628 individuals overall and divided across five age strata, each spanning 15 years. We identified variants associated with TB-BMD at 80 loci, of which 36 have not been previously identified; overall, they explain approximately 10% of the TB-BMD variance when combining all age groups and influence the risk of fracture. Pathway and enrichment analysis of the association signals showed clustering within gene sets implicated in the regulation of cell growth and SMAD proteins, overexpressed in the musculoskeletal system, and enriched in enhancer and promoter regions. These findings reveal TB-BMD as a relevant trait for genetic studies of osteoporosis, enabling the identification of variants and pathways influencing different bone compartments. Only variants in ESR1 and close proximity to RANKL showed a clear effect dependency on age. This most likely indicates that the majority of genetic variants identified influence BMD early in life and that their effect can be captured throughout the life course

An Integration of Genome-Wide Association Study and Gene Expression Profiling to Prioritize the Discovery of Novel Susceptibility Loci for Osteoporosis-Related Traits

Osteoporosis is a complex disorder and commonly leads to fractures in elderly persons. Genome-wide association studies (GWAS) have become an unbiased approach to identify variations in the genome that potentially affect health. However, the genetic variants identified so far only explain a small proportion of the heritability for complex traits. Due to the modest genetic effect size and inadequate power, true association signals may not be revealed based on a stringent genome-wide significance threshold. Here, we take advantage of SNP and transcript arrays and integrate GWAS and expression signature profiling relevant to the skeletal system in cellular and animal models to prioritize the discovery of novel candidate genes for osteoporosis-related traits, including bone mineral density (BMD) at the lumbar spine (LS) and femoral neck (FN), as well as geometric indices of the hip (femoral neck-shaft angle, NSA; femoral neck length, NL; and narrow-neck width, NW). A two-stage meta-analysis of GWAS from 7,633 Caucasian women and 3,657 men, revealed three novel loci associated with osteoporosis-related traits, including chromosome 1p13.2 (RAP1A, p = 3.6×10−8), 2q11.2 (TBC1D8), and 18q11.2 (OSBPL1A), and confirmed a previously reported region near TNFRSF11B/OPG gene. We also prioritized 16 suggestive genome-wide significant candidate genes based on their potential involvement in skeletal metabolism. Among them, 3 candidate genes were associated with BMD in women. Notably, 2 out of these 3 genes (GPR177, p = 2.6×10−13; SOX6, p = 6.4×10−10) associated with BMD in women have been successfully replicated in a large-scale meta-analysis of BMD, but none of the non-prioritized candidates (associated with BMD) did. Our results support the concept of our prioritization strategy. In the absence of direct biological support for identified genes, we highlighted the efficiency of subsequent functional characterization using publicly available expression profiling relevant to the skeletal system in cellular or whole animal models to prioritize candidate genes for further functional validation

Genetic Sharing with Cardiovascular Disease Risk Factors and Diabetes Reveals Novel Bone Mineral Density Loci.

Bone Mineral Density (BMD) is a highly heritable trait, but genome-wide association studies have identified few genetic risk factors. Epidemiological studies suggest associations between BMD and several traits and diseases, but the nature of the suggestive comorbidity is still unknown. We used a novel genetic pleiotropy-informed conditional False Discovery Rate (FDR) method to identify single nucleotide polymorphisms (SNPs) associated with BMD by leveraging cardiovascular disease (CVD) associated disorders and metabolic traits. By conditioning on SNPs associated with the CVD-related phenotypes, type 1 diabetes, type 2 diabetes, systolic blood pressure, diastolic blood pressure, high density lipoprotein, low density lipoprotein, triglycerides and waist hip ratio, we identified 65 novel independent BMD loci (26 with femoral neck BMD and 47 with lumbar spine BMD) at conditional FDR < 0.01. Many of the loci were confirmed in genetic expression studies. Genes validated at the mRNA levels were characteristic for the osteoblast/osteocyte lineage, Wnt signaling pathway and bone metabolism. The results provide new insight into genetic mechanisms of variability in BMD, and a better understanding of the genetic underpinnings of clinical comorbidity

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Large meta-analysis of genome-wide association studies identifies five loci for lean body mass

Lean body mass, consisting mostly of skeletal muscle, is important for healthy aging. We performed a genome-wide association study for whole body (20 cohorts of European ancestry with n = 38,292) and appendicular (arms and legs) lean body mass (n = 28,330) measured using dual energy X-ray absorptiometry or bioelectrical impedance analysis, adjusted for sex, age, height, and fat mass. Twenty-one single-nucleotide polymorphisms were significantly associated with lean body mass either genome wide (p < 5 x 10(-8)) or suggestively genome wide (p < 2.3 x 10(-6)). Replication in 63,475 (47,227 of European ancestry) individuals from 33 cohorts for whole body lean body mass and in 45,090 (42,360 of European ancestry) subjects from 25 cohorts for appendicular lean body mass was successful for five single-nucleotide polymorphisms in/ near HSD17B11, VCAN, ADAMTSL3, IRS1, and FTO for total lean body mass and for three single-nucleotide polymorphisms in/ near VCAN, ADAMTSL3, and IRS1 for appendicular lean body mass. Our findings provide new insight into the genetics of lean body mass

Phenotypic Characterization of a Major Quantitative Disease Resistance Locus for Partial Resistance to Phytophthora sojae

Major quantitative disease resistance loci (QDRLs) are rare in the Phytophthora sojae (Kaufmann and Gerdemann)–soybean [Glycine max (L). Merr.] pathosystem. A major QDRL on chromosome 18 (QDRL-18) was identified in PI 427105B and PI 427106. QDRL-18 represents a valuable resistance source for breeding programs. Thus, our objectives were to determine its isolate specificity and measure its effect on yield and resistance to both P. sojae and other soybean pathogens. We characterized near isogenic lines (NILs) developed from F7 recombinant inbred lines heterozygous at QDRL-18; NILs represent introgressions from PI 427105B, PI 427106, and susceptible ‘OX20- 8’. The introgressions from PI 427105B and PI 427106 increased resistance to P. sojae by 11 to 20% and 35 to 40%, respectively, based on laboratory and greenhouse assays, and increased yield by 13 to 29% under disease conditions. The resistant introgression from PI 427105B was also effective against seven P. sojae isolates with no isolate specificity detected. Based on quantitative polymerase chain reaction assays, NILs with the susceptible introgression had significantly higher relative levels of P. sojae colonization 48 h after inoculation. No pleiotropic effects for resistance to either soybean cyst nematode or Fusarium graminearum were detected. This information improves soybean breeders’ ability to make informed decisions regarding the deployment of QDRL-18 in their respective breeding programs

The effect of genome-wide association scan quality control on imputation outcome for common variants

Imputation is an extremely valuable tool in conducting and synthesising genome-wide association studies (GWASs). Directly typed SNP quality control (QC) is thought to affect imputation quality. It is, therefore, common practise to use quality-controlled (QCed) data as an input for imputing genotypes. This study aims to determine the effect of commonly applied QC steps on imputation outcomes. We performed several iterations of imputing SNPs across chromosome 22 in a dataset consisting of 3177 samples with Illumina 610k (Illumina, San Diego, CA, USA) GWAS data, applying different QC steps each time. The imputed genotypes were compared with the directly typed genotypes. In addition, we investigated the correlation between alternatively QCed data. We also applied a series of post-imputation QC steps balancing elimination of poorly imputed SNPs and information loss. We found that the difference between the unQCed data and the fully QCed data on imputation outcome was minimal. Our study shows that imputation of common variants is generally very accurate and robust to GWAS QC, which is not a major factor affecting imputation outcome. A minority of common-frequency SNPs with particular properties cannot be accurately imputed regardless of QC stringency. These findings may not generalise to the imputation of low frequency and rare variants.<br/