Semen contains relatively ill-defined regulatory components that likely aid fertilization, but which could also interfere with defense against infection. Each ejaculate contains trillions of exosomes, membrane-enclosed subcellular microvesicles, which have immunosuppressive effects on cells important in the genital mucosa. Exosomes in general are believed to mediate inter-cellular communication, possibly by transferring small RNA molecules. We found that seminal exosome (SE) preparations contain a substantial amount of RNA from 20 to 100 nucleotides (nts) in length. We sequenced 20–40 and 40–100 nt fractions of SE RNA separately from six semen donors. We found various classes of small non-coding RNA, including microRNA (21.7% of the RNA in the 20–40 nt fraction) as well as abundant Y RNAs and tRNAs present in both fractions. Specific RNAs were consistently present in all donors. For example, 10 (of ∼2600 known) microRNAs constituted over 40% of mature microRNA in SE. Additionally, tRNA fragments were strongly enriched for 5’-ends of 18–19 or 30–34 nts in length; such tRNA fragments repress translation. Thus, SE could potentially deliver regulatory signals to the recipient mucosa via transfer of small RNA molecules.

Annual influenza vaccinations are currently recommended for all individuals 6 months and older. Antibodies induced by vaccination are an important mechanism of protection against infection. Despite the overall public health success of influenza vaccination, many individuals fail to induce a substantial antibody response. Systems-level immune profiling studies have discerned associations between transcriptional and cell subset signatures with the success of antibody responses. However, existing signatures have relied on small cohorts and have not been validated in large independent studies. We leveraged multiple influenza vaccination cohorts spanning distinct geographical locations and seasons from the Human Immunology Project Consortium (HIPC) and the Center for Human Immunology (CHI) to identify baseline (i.e., before vaccination) predictive transcriptional signatures of influenza vaccination responses. Our multicohort analysis of HIPC data identified nine genes (RAB24, GRB2, DPP3, ACTB, MVP, DPP7, ARPC4, PLEKHB2, and ARRB1) and three gene modules that were significantly associated with the magnitude of the antibody response, and these associations were validated in the independent CHI cohort. These signatures were specific to young individuals, suggesting that distinct mechanisms underlie the lower vaccine response in older individuals. We found an inverse correlation between the effect size of signatures in young and older individuals. Although the presence of an inflammatory gene signature, for example, was associated with better antibody responses in young individuals, it was associated with worse responses in older individuals. These results point to the prospect of predicting antibody responses before vaccination and provide insights into the biological mechanisms underlying successful vaccination responses.

The X Chromosome plays an important role in human development and disease. However, functional genomic and disease association studies of X genes greatly lag behind autosomal gene studies, in part owing to the unique biology of X-Chromosome inactivation (XCI). Because of XCI, most genes are only expressed from one allele. Yet, ∼30% of X genes “escape” XCI and are transcribed from both alleles, many only in a proportion of the population. Such interindividual differences are likely to be disease relevant, particularly for sex-biased disorders. To understand the functional biology for X-linked genes, we developed X-Chromosome inactivation for RNA-seq (XCIR), a novel approach to identify escape genes using bulk RNA-seq data. Our method, available as an R package, is more powerful than alternative approaches and is computationally efficient to handle large population-scale data sets. Using annotated XCI states, we examined the contribution of X-linked genes to the disease heritability in the United Kingdom Biobank data set. We show that escape and variable escape genes explain the largest proportion of X heritability, which is in large part attributable to X genes with Y homology. Finally, we investigated the role of each XCI state in sex-biased diseases and found that although XY homologous gene pairs have a larger overall effect size, enrichment for variable escape genes is significantly increased in female-biased diseases. Our results, for the first time, quantitate the importance of variable escape genes for the etiology of sex-biased disease, and our pipeline allows analysis of larger data sets for a broad range of phenotypes.