Primula vulgaris (primrose) genome assembly, annotation and gene expression, with comparative genomics on the heterostyly supergene

Primula vulgaris (primrose) exhibits heterostyly: plants produce self-incompatible pin- or thrum-form flowers, with anthers and stigma at reciprocal heights. Darwin concluded that this arrangement promotes insect-mediated cross-pollination; later studies revealed control by a cluster of genes, or supergene, known as the S (Style length) locus. The P. vulgaris S locus is absent from pin plants and hemizygous in thrum plants (thrum-specific); mutation of S locus genes produces self-fertile homostyle flowers with anthers and stigma at equal heights. Here, we present a 411 Mb P. vulgaris genome assembly of a homozygous inbred long homostyle, representing ~87% of the genome. We annotate over 24,000 P. vulgaris genes, and reveal more genes up-regulated in thrum than pin flowers. We show reduced genomic read coverage across the S locus in other Primula species, including P. veris, where we define the conserved structure and expression of the S locus genes in thrum. Further analysis reveals the S locus has elevated repeat content (64%) compared to the wider genome (37%). Our studies suggest conservation of S locus genetic architecture in Primula, and provide a platform for identification and evolutionary analysis of the S locus and downstream targets that regulate heterostyly in diverse heterostylous species

Human physiologically based pharmacokinetic model for propofol

BACKGROUND: Propofol is widely used for both short-term anesthesia and long-term sedation. It has unusual pharmacokinetics because of its high lipid solubility. The standard approach to describing the pharmacokinetics is by a multi-compartmental model. This paper presents the first detailed human physiologically based pharmacokinetic (PBPK) model for propofol. METHODS: PKQuest, a freely distributed software routine , was used for all the calculations. The "standard human" PBPK parameters developed in previous applications is used. It is assumed that the blood and tissue binding is determined by simple partition into the tissue lipid, which is characterized by two previously determined set of parameters: 1) the value of the propofol oil/water partition coefficient; 2) the lipid fraction in the blood and tissues. The model was fit to the individual experimental data of Schnider et. al., Anesthesiology, 1998; 88:1170 in which an initial bolus dose was followed 60 minutes later by a one hour constant infusion. RESULTS: The PBPK model provides a good description of the experimental data over a large range of input dosage, subject age and fat fraction. Only one adjustable parameter (the liver clearance) is required to describe the constant infusion phase for each individual subject. In order to fit the bolus injection phase, for 10 or the 24 subjects it was necessary to assume that a fraction of the bolus dose was sequestered and then slowly released from the lungs (characterized by two additional parameters). The average weighted residual error (WRE) of the PBPK model fit to the both the bolus and infusion phases was 15%; similar to the WRE for just the constant infusion phase obtained by Schnider et. al. using a 6-parameter NONMEM compartmental model. CONCLUSION: A PBPK model using standard human parameters and a simple description of tissue binding provides a good description of human propofol kinetics. The major advantage of a PBPK model is that it can be used to predict the changes in kinetics produced by variations in physiological parameters. As one example, the model simulation of the changes in pharmacokinetics for morbidly obese subjects is discussed