A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically-determined protein-protein networks

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

Identification of the PP2C gene family in paper mulberry (Broussonetia papyrifera) and its roles in the regulation mechanism of the response to cold stress

OBJECTIVES

To study the possible roles of type-2C protein phosphatases (PP2Cs) which have been confirmed to play roles in the response to diverse abiotic stresses in paper mulberry, we launched a series of genomic and functional studies of BpPP2Cs.

RESULTS

Sixty-three PP2C proteins in paper mulberry (Broussonetia papyrifera) were classified into 13 clades. Four BpPP2Cs with kinase domains were verified to be highly conserved in organisms ranging from algae to dicots. Seven pairs of BpPP2C genes were found to be expanding, and 18 BpPP2C genes had orthologues in Arabidopsis. BpPP2Cs showed broad expression in different tissues; the expression levels of 18 BpPP2Cs were changed and the phosphorylation levels of seven BpPP2C proteins increased at low temperature. Cold-response elements were found in the promoter region of 31 BpPP2Cs. Finally, Bp01g0320 was found to act as a hub protein and Bp01g0512 and Bp09g1278 played key roles in the ABA-signaling pathway and MAPK cascades, respectively.

CONCLUSION

These results suggest that the PP2C gene family of paper mulberry is evolutionarily conserved and participates the regulation of the response to cold stress, which will play a vital role in further research on phosphatases in paper mulberry.

Microarray analysis identification of key pathways and interaction network of differential gene expressions during osteogenic differentiation

BACKGROUND

Adult bone marrow-derived mesenchymal stem cells (BM-MSCs) are multipotent stem cells that can differentiate into three lineages. They are suitable sources for cell-based therapy and regenerative medicine applications. This study aims to evaluate the hub genes and key pathways of differentially expressed genes (DEGs) related to osteogenesis by bioinformatics analysis in three different days. The DEGs were derived from the three different days compared with day 0.

RESULTS

Gene expression profiles of GSE37558 were obtained from the Gene Expression Omnibus (GEO) database. A total of 4076 DEGs were acquired on days 8, 12, and 25. Gene ontology (GO) enrichment analysis showed that the non-canonical Wnt signaling pathway and lipopolysaccharide (LPS)-mediated signaling pathway were commonly upregulated DEGs for all 3 days. KEGG pathway analysis indicated that the PI3K-Akt and focal adhesion were also commonly upregulated DEGs for all 3 days. Ten hub genes were identified by CytoHubba on days 8, 12, and 25. Then, we focused on the association of these hub genes with the Wnt pathways that had been enriched from the protein-protein interaction (PPI) by the Cytoscape plugin MCODE.

CONCLUSIONS

These findings suggested further insights into the roles of the PI3K/AKT and Wnt pathways and their association with osteogenesis. In addition, the stem cell microenvironment via growth factors, extracellular matrix (ECM), IGF1, IGF2, LPS, and Wnt most likely affect osteogenesis by PI3K/AKT.