Functional Genomics Complements Quantitative Genetics in Identifying Disease-Gene Associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype

Activation of ERK and NF-κB during HARE-Mediated Heparin Uptake Require Only One of the Four Endocytic Motifs

We thank Bruce A. Baggenstoss and Jennifer L. Washburn for technical support in many experiments and Emma K. Blank, Andrew W. Egger, Brianna M. Kellar and Helen T. Russom for assistance with experiments supporting Fig 2.Fifteen different ligands, including heparin (Hep), are cleared from lymph and blood by the Hyaluronan (HA) Receptor for Endocytosis (HARE; derived from Stabilin-2 by proteolysis), which contains four endocytic motifs (M1-M4). Endocytosis of HARE•Hep complexes is targeted to coated pits by M1, M2, and M3 (Pandey et al, Int. J. Cell Biol. 2015, article ID 524707), which activates ERK1/2 and NF-κB (Pandey et al J. Biol. Chem. 288, 14068–79, 2013). Here, we used a NF-κB promoter-driven luciferase gene assay and cell lines expressing different HARE cytoplasmic domain mutants to identify motifs needed for Hep-mediated signaling. Deletion of M1, M2 or M4 singly had no effect on Hep-mediated ERK1/2 activation, whereas signaling (but not uptake) was eliminated in HARE(ΔM3) cells lacking NPLY2519. ERK1/2 signaling in cells expressing WT HARE(Y2519A) or HARE(Y2519A) lacking M1, M2 and M4 (containing M3-only) was decreased by 75% or eliminated, respectively. Deletion of M3 (but not M1, M2 or M4) also inhibited the formation of HARE•Hep•ERK1/2 complexes by 67%. NF-κB activation by HARE-mediated uptake of Hep, HA, dermatan sulfate or acetylated LDL was unaffected in single-motif deletion mutants lacking M1, M2 or M4. In contrast, cells expressing HARE(ΔM3) showed loss of HARE-mediated NF-κB activation during uptake of each of these four ligands. NF-κB activation by the four signaling ligands was also eliminated in HARE(Y2519A) or HARE(M3-only;Y2519A) cells. We conclude that the HARE NPLY2519 motif is necessary for both ERK1/2 and NF-κB signaling and that Tyr2519 is critical for these functions.Yeshttp://www.plosone.org/static/editorial#pee