The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics, however the underlying molecular mechanisms of these differences remain largely unknown. Here, we present an extensive catalog of both sex differences in gene expression and its genetic regulation across 44 human tissue sources surveyed by GTEx (v8 release). We demonstrate that sex strongly influences gene expression levels and cellular composition of tissue samples across the human body. The effect of sex on gene expression is widespread, with a total of 37% of all genes exhibiting sex-biased expression in at least one tissue. This suggests that many if not most biological processes, and thus complex traits and diseases, are impacted by sex effects on the transciptome. We expand the identification of cis-eQTLs with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation in a single sex, including novel associations not detected with sex-agnostic approaches. Altogether we provide the most comprehensive characterization of sex differences in the human transcriptome and its regulation to date.Peer ReviewedPreprin

Cell type-specific genetic regulation of gene expression across human tissues

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue

The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation

Selective rearrangement of terminal epoxides into methylketones catalysed by a nucleophilic rhodium-NHC-pincer complex

An efficient RhI–NHC–pincer catalyst for the highly regioselective Meinwald rearrangement of monoalkylated epoxides into methylketones under mild conditions is presented. The nucleophilic epoxide opening is assisted by Lewis acids

Steady-state statistical sputtering model for extracting depth profiles from molecular dynamics simulations of dynamic SIMS

Recently a "divide and conquer" approach was developed to model by molecular dynamics (MD) simulations dynamic secondary ion mass spectrometry (SIMS) experiments in order to understand the important factors for depth profiling. Although root-mean-square (rms) roughness can be directly calculated from the simulations, calculating depth profiles is beyond the current capability of the MD simulations. The statistical sputtering model (SSM) of Krantzman and Wucher establishes the foundation for connecting information from the MD simulations to depth profiles. In this study, we revise the SSM to incorporate more extensive information from the MD simulations in the steady-state region, thus presenting the steady-state statistical sputtering model (SS-SSM). The revised model is utilized to interpret MD simulations of 20 keV C60 bombardment of Ag at normal incidence as well as the effect of sample rotation on depth profiling