RAFFI: Accurate and fast familial relationship inference in large scale biobank studies using RaPID

Inference of relationships from whole-genome genetic data of a cohort is a crucial prerequisite for genome-wide association studies. Typically, relationships are inferred by computing the kinship coefficients (ϕ) and the genome-wide probability of zero IBD sharing (π₀) among all pairs of individuals. Current leading methods are based on pairwise comparisons, which may not scale up to very large cohorts (e.g., sample size >1 million). Here, we propose an efficient relationship inference method, RAFFI. RAFFI leverages the efficient RaPID method to call IBD segments first, then estimate the ϕ and π₀ from detected IBD segments. This inference is achieved by a data-driven approach that adjusts the estimation based on phasing quality and genotyping quality. Using simulations, we showed that RAFFI is robust against phasing/genotyping errors, admix events, and varying marker densities, and achieves higher accuracy compared to KING, the current leading method, especially for more distant relatives. When applied to the phased UK Biobank data with ~500K individuals, RAFFI is approximately 18 times faster than KING. We expect RAFFI will offer fast and accurate relatedness inference for even larger cohorts.     

Inventing Engineered Organoids for end-stage liver failure patients

Journal of Molecular Histology - End-stage liver disease (ESLD) is a term used clinically in reference to a group of liver diseases with liver transplantation as the choice of treatment. Due to the...     

13C tracer experiments and metabolite balancing for metabolic flux analysis: comparing two approaches

Conventional metabolic flux analysis uses the information gained from determination of measurable fluxes and a steady-state assumption for intracellular metabolites to calculate the metabolic fluxes in a given metabolic network. The determination of intracellular fluxes depends heavily on the correctness of the assumed stoichiometry including the presence of all reactions with a noticeable impact on the model metabolite balances. Determination of fluxes in complex metabolic networks often requires the inclusion of NADH and NADPH balances, which are subject to controversial debate. Transhydrogenation reactions that transfer reduction equivalents from NADH to NADPH or vice versa can usually not be included in the stoichiometric model, because they result in singularities in the stoichiometric matrix. However, it is the NADPH balance that, to a large extent, determines the calculated flux through the pentose phosphate pathway. Hence, wrong assumptions on the presence or activity of transhydrogenation reactions will result in wrong estimations of the intracellular flux distribution. Using 13C tracer experiments and NMR analysis, flux analysis can be performed on the basis of only well established stoichiometric equations and measurements of the labeling state of intracellular metabolites. Neither NADH/NADPH balancing nor assumptions on energy yields need to be included to determine the intracellular fluxes. Because metabolite balancing methods and the use of 13C labeling measurements are two different approaches to the determination of intracellular fluxes, both methods can be used to verify each other or to discuss the origin and significance of deviations in the results. Flux analysis based entirely on metabolite balancing and flux analysis, including labeling information, have been performed independently for a wild-type strain of Aspergillus oryzae producing alpha-amylase. Two different nitrogen sources, NH4+ and NO3-, have been used to investigate the influence of the NADPH requirements on the intracellular flux distribution. The two different approaches to the calculation of fluxes are compared and deviations in the results are discussed. Copyright 1998 John Wiley & Sons, Inc.     

Histopathological biomarkers and genotoxicity in gill and liver tissues of Nile tilapia Oreochromis niloticus from a polluted part of the Nile River,Egypt

Fish health is affected by water pollution. Oreochromis niloticus collected during summer 2014 from El-Serw, a polluted site on the Nile River, were compared with fish from a reference site, El-Zamalek. Histopathological changes were detected in gill and liver tissue samples using light and electron microscopy. In addition, the degree of DNA damage was measured using the comet assay. To indicate the severity of water pollution at the two sites, physico-chemical properties and heavy metal concentrations were investigated. Gill damage, including lamellar cell hyperplasia and aneurysm, was observed in the fish samples from the polluted site. The livers of fish from the polluted area showed necrosis and an increase in melanomacrophage centres. Histochemical results confirmed a marked rise of gill mucopolysaccharides and a reduction of carbohydrate stored in hepatocytes. Electron microscopy revealed clear alterations in gill and liver tissue of fish from the polluted site. The comet assay showed highly significant DNA damage in tilapia collected from the polluted site, compared to those from the reference site. Histopathological biomarkers and the comet assay may therefore be sensitive indicators of exposure to mixtures of aquatic pollutants in Nile tilapia.