Sin4 and Rgrl proteins, previously shown by genetic studies to play both positive and negative roles in the transcriptional regulation of many genes, are identified here as components of mediator and RNA polymerase II holoenzyme complexes. Results with Sin4 deletion and Rgrl truncation strains indicate the association of these proteins in a subcomplex comprising Sin4, Rgrl, Galll, and a 50-kDa polypeptide. Taken together with the previous genetic evidence, our findings point to a role of the mediator in repression as well as in transcriptional activation. tory effects are sometimes seen at the same promoter. Sin4, like Rgrl, is required for repression of glucose-regulated genes, and both proteins are required for maximal induction of these genes as well (13).Here we report biochemical connections that may underlie the genetic similarities GAl1, SIN4, and RGR1. Our findings further indicate how the paradox of both positive and negative control by Galll, Sin4, and Rgrl proteins may be resolved. Finally, there are implications for the structure and role of the mediator complex in transcriptional regulation.

Here we present a Joint-Tissue Imputation (JTI) approach and a Mendelian Randomization (MR) framework for causal inference, MR-JTI. JTI borrows information across transcriptomes of different tissues, leveraging shared genetic regulation, to improve prediction performance in a tissue-dependent manner. Notably, JTI includes single-tissue imputation PrediXcan as a special case and outperforms other single-tissue approaches (BSLMM and Dirichlet Process Regression). MR-JTI models variant-level heterogeneity (primarily due to horizontal pleiotropy, addressing a major challenge of TWAS interpretation) and performs causal inference with type-I error control. We make explicit the connection between the genetic architecture of gene expression and of complex traits, and the suitability of MR as a causal inference strategy for TWAS. We provide a resource of imputation models generated from GTEx and PsychENCODE panels. Analysis of biobanks and meta-analysis data and extensive simulations show substantially improved statistical power, replication, and causal mapping rate for JTI relative to existing approaches.

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Currently, many studies on neuropsychiatric disorders have utilized massive trio-based whole-exome sequencing (WES) and whole-genome sequencing (WGS) to identify numerous de novo mutations (DNMs). Here, we retrieved 17,104 DNMs from 3,555 trios across four neuropsychiatric disorders: autism spectrum disorder (ASD), epileptic encephalopathy (EE), intellectual disability (ID), schizophrenia (SCZ), in addition to unaffected siblings (Control), from 36 studies by WES/WGS. After eliminating non-exonic variants, we focused on 3,334 exonic DNMs for evaluation their association with these diseases. Our results revealed a higher prevalence of DNMs in the probands of all four disorders than the one in the controls (P < 1.3 × 10-7). The elevated DNM frequency is dominated by loss-of-function/deleterious single nucleotide variants and frameshift indels (i.e., extreme mutations, P < 4.5 × 10-5). With extensive annotation of these “extreme” mutations, we prioritized 764 candidate genes in these four disorders. A combined analysis of Gene Ontology, microRNA targets, and transcription factor targets revealed shared biological process and non-coding regulatory elements of candidate genes in the pathology of neuropsychiatric disorders. In addition, weighted gene co-expression network analysis (WGCNA) of human laminar-specific neocortical expression data showed that candidate genes are convergent on eight shared modules with specific layer-enrichment and biological process features. Furthermore, we identified that 53 candidate genes are associated with more than one disorder (P < 0.000001), suggesting a possibly shared genetic etiology underlying these disorders. Particularly, DNMs of the SCN2A gene are frequently occurred across all four disorders. Finally, we constructed a freely available NPdenovo database, which provides a comprehensive catalog of the DNMs identified in neuropsychiatric disorders.