Genome-wide Association Mapping of Qualitatively Inherited Traits in a Germplasm Collection

Genome-wide association (GWA) has been used as a tool for dissecting the genetic architecture of quantitatively inherited traits. We demonstrate here that GWA can also be highly useful for detecting many major genes governing categorically defined phenotype variants that exist for qualitatively inherited traits in a germplasm collection. Genome-wide association mapping was applied to categorical phenotypic data available for 10 descriptive traits in a collection of ~13,000 soybean [Glycine max (L.) Merr.] accessions that had been genotyped with a 50,000 single nucleotide polymorphism (SNP) chip. A GWA on a panel of accessions of this magnitude can offer substantial statistical power and mapping resolution, and we found that GWA mapping resulted in the identification of strong SNP signals for 24 classical genes as well as several heretofore unknown genes controlling the phenotypic variants in those traits. Because some of these genes had been cloned, we were able to show that the narrow GWA mapping SNP signal regions that we detected for the phenotypic variants had chromosomal bp spans that, with just one exception, overlapped the bp region of the cloned genes, despite local variation in SNP number and nonuniform SNP distribution in the chip set

Dissecting the Genetic Basis of Local Adaptation in Soybean

Soybean (Glycine max) is the most widely grown oilseed in the world and is an important source of protein for both humans and livestock. Soybean is widely adapted to both temperate and tropical regions, but a changing climate demands a better understanding of adaptation to specific environmental conditions. Here, we explore genetic variation in a collection of 3,012 georeferenced, locally adapted landraces from a broad geographical range to help elucidate the genetic basis of local adaptation. We used geographic origin, environmental data and dense genome-wide SNP data to perform an environmental association analysis and discover loci displaying steep gradients in allele frequency across geographical distance and between landrace and modern cultivars. Our combined application of methods in environmental association mapping and detection of selection targets provide a better understanding of how geography and selection may have shaped genetic variation among soybean landraces. Moreover, we identified several important candidate genes related to drought and heat stress, and revealed important genomic regions possibly involved in the geographic divergence of soybean

Lead exposure of mainland Australia\u27s top avian predator

Lead (Pb) toxicity, through ingestion of lead ammunition in carcasses, is a threat to scavenging birds worldwide, but has received little attention in Australia. We analyzed lead exposure in the wedge-tailed eagle (Aquila audax), the largest raptor species found in mainland Australia and a facultative scavenger. Eagle carcasses were collected opportunistically throughout south-eastern mainland Australia between 1996 and 2022. Lead concentrations were measured in bone samples from 62 animals via portable X-ray fluorescence (XRF). Lead was detected (concentration \u3e 1 ppm) in 84% (n = 52) of the bone samples. The mean lead concentration of birds in which lead was detected was 9.10 ppm (±SE 1.66). Bone lead concentrations were elevated (10–20 ppm) in 12.9% of samples, and severe ( \u3e 20 ppm) in 4.8% of samples. These proportions are moderately higher than equivalent data for the same species from the island of Tasmania, and are comparable to data from threatened eagle species from other continents. Lead exposure at these levels is likely to have negative impacts on wedge-tailed eagles at the level of the individual and perhaps at a population level. Our results suggest that studies of lead exposure in other Australian avian scavenger species are warranted

Distinguishing grade I meningioma from higher grade meningiomas without biopsy

BACKGROUND: Many meningiomas are identified by imaging and followed, with an assumption that they are WHO Grade I tumors. The purpose of our investigation is to find clinical or imaging predictors of WHO Grade II/III tumors to distinguish them from Grade I meningiomas. METHODS: Patients with a pathologic diagnosis of meningioma from 2002-2009 were included if they had pre-operative MRI studies and pathology for review. A Neuro-Pathologist reviewed and classified all tumors by WHO 2007. All Brain MRI imaging was reviewed by a Neuro-radiologist. Pathology and Radiology reviews were blinded from each other and clinical course. Recursive partitioning was used to create predictive models for identifying meningioma grades. RESULTS: Factors significantly correlating with a diagnosis of WHO Grade II-III tumors in univariate analysis: prior CVA (p = 0.005), CABG (p = 0.010), paresis (p = 0.008), vascularity index = 4/4: (p = 0.009), convexity vs other (p = 0.014), metabolic syndrome (p = 0.025), non-skull base (p = 0.041) and non-postmenopausal female (p = 0.045). Recursive partitioning analysis identified four categories: 1. prior CVA, 2. vascular index (vi) = 4 (no CVA), 3. premenopausal or male, vi \u3c 4, no CVA. 4. Postmenopausal, vi \u3c 4, no CVA with corresponding rates of 73, 54, 35 and 10% of being Grade II-III meningiomas. CONCLUSIONS: Meningioma patients with prior CVA and those grade 4/4 vascularity are the most likely to have WHO Grade II-III tumors while post-menopausal women without these features are the most likely to have Grade I meningiomas. Further study of the associations of clinical and imaging factors with grade and clinical behavior are needed to better predict behavior of these tumors without biopsy

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Finding Our Way through Phenotypes

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility

Factors Associated with Revision Surgery after Internal Fixation of Hip Fractures

Background: Femoral neck fractures are associated with high rates of revision surgery after management with internal fixation. Using data from the Fixation using Alternative Implants for the Treatment of Hip fractures (FAITH) trial evaluating methods of internal fixation in patients with femoral neck fractures, we investigated associations between baseline and surgical factors and the need for revision surgery to promote healing, relieve pain, treat infection or improve function over 24 months postsurgery. Additionally, we investigated factors associated with (1) hardware removal and (2) implant exchange from cancellous screws (CS) or sliding hip screw (SHS) to total hip arthroplasty, hemiarthroplasty, or another internal fixation device. Methods: We identified 15 potential factors a priori that may be associated with revision surgery, 7 with hardware removal, and 14 with implant exchange. We used multivariable Cox proportional hazards analyses in our investigation. Results: Factors associated with increased risk of revision surgery included: female sex, [hazard ratio (HR) 1.79, 95% confidence interval (CI) 1.25-2.50; P = 0.001], higher body mass index (fo

Genome-wide Association Mapping of Qualitatively Inherited Traits in a Germplasm Collection

Genome-wide association (GWA) has been used as a tool for dissecting the genetic architecture of quantitatively inherited traits. We demonstrate here that GWA can also be highly useful for detecting many major genes governing categorically defined phenotype variants that exist for qualitatively inherited traits in a germplasm collection. Genome-wide association mapping was applied to categorical phenotypic data available for 10 descriptive traits in a collection of ~13,000 soybean [Glycine max (L.) Merr.] accessions that had been genotyped with a 50,000 single nucleotide polymorphism (SNP) chip. A GWA on a panel of accessions of this magnitude can offer substantial statistical power and mapping resolution, and we found that GWA mapping resulted in the identification of strong SNP signals for 24 classical genes as well as several heretofore unknown genes controlling the phenotypic variants in those traits. Because some of these genes had been cloned, we were able to show that the narrow GWA mapping SNP signal regions that we detected for the phenotypic variants had chromosomal bp spans that, with just one exception, overlapped the bp region of the cloned genes, despite local variation in SNP number and nonuniform SNP distribution in the chip set

Dissecting the Genetic Basis of Local Adaptation in Soybean

Soybean (Glycine max) is the most widely grown oilseed in the world and is an important source of protein for both humans and livestock. Soybean is widely adapted to both temperate and tropical regions, but a changing climate demands a better understanding of adaptation to specific environmental conditions. Here, we explore genetic variation in a collection of 3,012 georeferenced, locally adapted landraces from a broad geographical range to help elucidate the genetic basis of local adaptation. We used geographic origin, environmental data and dense genome-wide SNP data to perform an environmental association analysis and discover loci displaying steep gradients in allele frequency across geographical distance and between landrace and modern cultivars. Our combined application of methods in environmental association mapping and detection of selection targets provide a better understanding of how geography and selection may have shaped genetic variation among soybean landraces. Moreover, we identified several important candidate genes related to drought and heat stress, and revealed important genomic regions possibly involved in the geographic divergence of soybean