Lrp13 is a novel vertebrate lipoprotein receptor that binds vitellogenins in teleost fishes.

Transcripts encoding a novel member of the lipoprotein receptor superfamily, termed LDL receptor-related protein (Lrp)13, were sequenced from striped bass (Morone saxatilis) and white perch (Morone americana) ovaries. Receptor proteins were purified from perch ovary membranes by protein-affinity chromatography employing an immobilized mixture of vitellogenins Aa and Ab. RT-PCR revealed lrp13 to be predominantly expressed in striped bass ovary, and in situ hybridization detected lrp13 transcripts in the ooplasm of early secondary growth oocytes. Quantitative RT-PCR confirmed peak lrp13 expression in the ovary during early secondary growth. Quantitative mass spectrometry revealed peak Lrp13 protein levels in striped bass ovary during late-vitellogenesis, and immunohistochemistry localized Lrp13 to the oolemma and zona radiata of vitellogenic oocytes. Previously unreported orthologs of lrp13 were identified in genome sequences of fishes, chicken (Gallus gallus), mouse (Mus musculus), and dog (Canis lupus familiaris). Zebrafish (Danio rerio) and Nile tilapia (Oreochromis niloticus) lrp13 loci are discrete and share genomic synteny. The Lrp13 appears to function as a vitellogenin receptor and may be an important mediator of yolk formation in fishes and other oviparous vertebrates. The presence of lrp13 orthologs in mammals suggests that this lipoprotein receptor is widely distributed among vertebrates, where it may generally play a role in lipoprotein metabolism.

Systems genomics of metabolic phenotypes in wild-type Drosophila melanogaster.

Systems biology is an approach to dissection of complex traits that explicitly recognizes the impact of genetic, physiological, and environmental interactions in the generation of phenotypic variation. We describe comprehensive transcriptional and metabolic profiling in Drosophila melanogaster across four diets, finding little overlap in modular architecture. Genotype and genotype-by-diet interactions are a major component of transcriptional variation (24 and 5.3% of the total variation, respectively) while there were no main effects of diet (<1%). Genotype was also a major contributor to metabolomic variation (16%), but in contrast to the transcriptome, diet had a large effect (9%) and the interaction effect was minor (2%) for the metabolome. Yet specific principal components of these molecular phenotypes measured in larvae are strongly correlated with particular metabolic syndrome-like phenotypes such as pupal weight, larval sugar content and triglyceride content, development time, and cardiac arrhythmia in adults. The second principal component of the metabolomic profile is especially informative across these traits with glycine identified as a key loading variable. To further relate this physiological variability to genotypic polymorphism, we performed evolve-and-resequence experiments, finding rapid and replicated changes in gene frequency across hundreds of loci that are specific to each diet. Adaptation to diet is thus highly polygenic. However, loci differentially transcribed across diet or previously identified by RNAi knockdown or expression QTL analysis were not the loci responding to dietary selection. Therefore, loci that respond to the selective pressures of diet cannot be readily predicted a priori from functional analyses.