PAR6, A Potential Marker for the Germ Cells Selected to Form Primordial Follicles in Mouse Ovary

Partitioning-defective proteins (PAR) are detected to express mainly in the cytoplast, and play an important role in cell polarity. However, we showed here that PAR6, one kind of PAR protein, was localized in the nuclei of mouse oocytes that formed primordial follicles during the perinatal period, suggesting a new role of PAR protein. It is the first time we found that, in mouse fetal ovaries, PAR6 appeared in somatic cell cytoplasm and fell weak when somatic cells invaded germ cell cysts at 17.5 days post coitus (dpc). Meanwhile, the expression of PAR6 was observed in cysts, and became strong in the nuclei of some germ cells at 19.5 dpc and all primordial follicular oocytes at 3 day post parturition (dpp), and then obviously declined when the primordial follicles entered the folliculogenic growth phase. During the primordial follicle pool foundation, the number of PAR6 positive germ cells remained steady and was consistent with that of formed follicles at 3 dpp. There were no TUNEL (apoptosis examination) positive germ cells stained with PAR6 at any time studied. The number of follicles significantly declined when 15.5 dpc ovaries were treated with the anti-PAR6 antibody and PAR6 RNA interference. Carbenoxolone (CBX, a known blocker of gap junctions) inhibited the expression of PAR6 in germ cells and the formation of follicles. Our results suggest that PAR6 could be used as a potential marker of germ cells for the primordial follicle formation, and the expression of PAR6 by a gap junction-dependent process may contribute to the formation of primordial follicles and the maintenance of oocytes at the diplotene stage

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H

EXA-2017-1S-GESTIÓN DE NEGOCIOS ELECTRÓNICOS-381-2Par.docx

Raw image under the illumination of laser Originally published in Optics Letters on 01 February 2017 (ol-42-3-635

Pathway Analysis Integrating Genome-Wide and Functional Data Identifies PLCG2 as a Candidate Gene for Age-Related Macular Degeneration

PURPOSE. Age-related macular degeneration (AMD) is the worldwide leading cause of blindness among the elderly. Although genome-wide association studies (GWAS) have identified AMD risk variants, their roles in disease etiology are not well-characterized, and they only explain a portion of AMD heritability. METHODS. We performed pathway analyses using summary statistics from the International AMD Genomics Consortium's 2016 GWAS and multiple pathway databases to identify biological pathways wherein genetic association signals for AMD may be aggregating. We determined which genes contributed most to significant pathway signals across the databases. We characterized these genes by constructing protein-protein interaction networks and performing motif analysis. RESULTS. We determined that eight genes (C2, C3, LIPC, MICA, NOTCH4, PLCG2, PPARA, and RAD51B) drive'' the statistical signals observed across pathways curated in the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, and Gene Ontology (GO) databases. We further refined our definition of statistical driver gene to identify PLCG2 as a candidate gene for AMD due to its significant gene-level signals (P < 0.0001) across KEGG, Reactome, GO, and NetPath pathways. CONCLUSIONS. We performed pathway analyses on the largest available collection of advanced AMD cases and controls in the world. Eight genes strongly contributed to significant pathways from the three larger databases, and one gene (PLCG2) was central to significant pathways from all four databases. This is, to our knowledge, the first study to identify PLCG2 as a candidate gene for AMD based solely on genetic burden. Our findings reinforce the utility of integrating in silico genetic and biological pathway data to investigate the genetic architecture of AMD