Selective phenotyping, entropy reduction, and the mastermind game.

BACKGROUND: With the advance of genome sequencing technologies, phenotyping, rather than genotyping, is becoming the most expensive task when mapping genetic traits. The need for efficient selective phenotyping strategies, i.e. methods to select a subset of genotyped individuals for phenotyping, therefore increases. Current methods have focused either on improving the detection of causative genetic variants or their precise genomic location separately. RESULTS: Here we recognize selective phenotyping as a Bayesian model discrimination problem and introduce SPARE (Selective Phenotyping Approach by Reduction of Entropy). Unlike previous methods, SPARE can integrate the information of previously phenotyped individuals, thereby enabling an efficient incremental strategy. The effective performance of SPARE is demonstrated on simulated data as well as on an experimental yeast dataset. CONCLUSIONS: Using entropy reduction as an objective criterion gives a natural way to tackle both issues of detection and localization simultaneously and to integrate intermediate phenotypic data. We foresee entropy-based strategies as a fruitful research direction for selective phenotyping

Evaluating openEHR for storing computable representations of electronic health record phenotyping algorithms

Electronic Health Records (EHR) are data generated during routine clinical care. EHR offer researchers unprecedented phenotypic breadth and depth and have the potential to accelerate the pace of precision medicine at scale. A main EHR use-case is creating phenotyping algorithms to define disease status, onset and severity. Currently, no common machine-readable standard exists for defining phenotyping algorithms which often are stored in human-readable formats. As a result, the translation of algorithms to implementation code is challenging and sharing across the scientific community is problematic. In this paper, we evaluate openEHR, a formal EHR data specification, for computable representations of EHR phenotyping algorithms.Comment: 30th IEEE International Symposium on Computer-Based Medical Systems - IEEE CBMS 201

Crop ontology in support of conservation and use of banana genetic resources

Poster presented at Workshop on Crop Ontology and Phenotyping Data Interoperability. Montpellier (France), 31 Mar-4 Apr 201

Why dried blood spots are an ideal tool for CYP1A2 phenotyping

Background and Objective: Dried blood spot (DBS) sampling has gained wide interest in bioanalysis during the last decade and has already been successfully applied in pharmacokinetic and phenotyping studies. However, all of the available phenotyping studies used small datasets and did not include a systematic evaluation of DBS-specific parameters. The latter is important since several of these factors still challenge the breakthrough of DBS in routine practice. In this study, caffeine and paraxanthine are determined in capillary DBS, venous DBS, whole blood and plasma for cytochrome P450 (CYP) 1A2 phenotyping. The aim of this study was to explore the usefulness of DBS as a tool for CYP1A2 phenotyping. Methods: A CYP1A2 phenotyping study was conducted in 73 healthy volunteers who received a 150 mg oral dose of caffeine. Six hours post-administration, caffeine and paraxanthine concentrations and paraxanthine:caffeine molar concentration ratios, i.e., the actual CYP1A2 phenotyping indices, were determined in capillary DBS (obtained by non-volumetric application, direct from the fingertip), venous DBS, whole blood, and plasma. Furthermore, the impact of DBS-specific parameters, including hematocrit, volume spotted, and punch location, was evaluated. Results: Concentrations of caffeine and paraxanthine in capillary DBS were, respectively, on average 12.7 and 13.8 % lower than those in venous DBS and 31.5 and 33.1 % lower than those in plasma. While these differences were statistically significant (p = 0.053). This ratio also alleviated the impact of hematocrit and volume spotted. Conclusions: Using the largest DBS-based phenotyping study to date, we have demonstrated that CYP1A2 phenotyping in capillary DBS is a valid and convenient alternative for the classical plasma-based approach. Additionally, we have provided an objective basis as to why DBS are an ideal tool for CYP1A2 phenotyping

Modeling neurocognitive and neurobiological recovery in addiction

This book focuses on "what to know" and "how to apply" information, prioritizing novel principles and delineating cutting-edge assessment, phenotyping and treatment tools

Monitoring drought responses of barley genotypes with semi-robotic phenotyping platform and association analysis between recorded traits and allelic variants of some stress genes

Genetic improvement of complex traits such as drought adaptation can be advanced by the combination of genomic and phenomic approaches. Semi-robotic phenotyping platform was used for computer-controlled watering, digital and thermal imaging of barley plants grown in greenhouse. The tested barley variants showed 0–76% reduction in green pixel-based shoot surface area in soil with 20% water content, compared to well-watered plants grown in soil with 60% water content. The barley HvA1 gene encoding the group 3 LEA (Late Embryogenesis Abundant) protein exhibited four (A–D) haplotypes as identified by the EcoTILLING and subsequent DNA sequencing. The green pixel mean value of genotypes with haplotype D was higher than the mean value of the remaining haplotypes, indicating a pivotal role of haplotype D in optimizing the green biomass production under drought condition. In water limitation, the canopy temperature of a highly sensitive genotype was 18.0°C, as opposed to 16.9°C of leaves from a tolerant genotype as measured by thermal imaging. Drought-induced changes in leaf temperature showed moderate correlation with the water use efficiency (r2 = 0.431). The haplotype/trait association analysis based on the t-test has revealed a positive effect of a haplotype B (SNPs:GCCCCTGC) in a gene encoding the barley fungal pathogen induced mRNA for pathogen-related protein (HvPPRPX), on harvest index, thousand grain weight, water use efficiency and grain yield. The presented pilot study established a basic methodology for the integrated use of phenotyping and haplotyping data in characterization of genotype-dependent drought responses in barley