The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships 1,2 . Here, we present a human "all-by-all" reference interactome map of human binary protein interactions, or "HuRI". With ~53,000 high-quality protein-protein interactions (PPIs), HuRI has approximately four times more such interactions than high-quality curated interactions from smallscale studies. Integrating HuRI with genome 3 , transcriptome 4 , and proteome 5 data enables the study of cellular function within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying specific subcellular roles of PPIs. Inferred tissuespecific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms underlying tissue-specific phenotypes of Mendelian Reprints and permissions information is available at http://www.nature.com/reprints.Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms

Genes and proteins generate molecular circuitry that enables the cell to process information and respond to stimuli. A major challenge is to identify characteristic patterns in this network of interactions that may shed light on basic cellular mechanisms. Previous studies have analyzed aspects of this network, concentrating on either transcription-regulation or protein-protein interactions. Here we search for composite network motifs: characteristic network patterns consisting of both transcription-regulation and protein-protein interactions that recur significantly more often than in random networks. To this end we developed algorithms for detecting motifs in networks with two or more types of interactions and applied them to an integrated data set of proteinprotein interactions and transcription regulation in Saccharomyces cerevisiae. We found a two-protein mixed-feedback loop motif, five types of three-protein motifs exhibiting coregulation and complex formation, and many motifs involving four proteins. Virtually all four-protein motifs consisted of combinations of smaller motifs. This study presents a basic framework for detecting the building blocks of networks with multiple types of interactions.

Cells respond to stimuli by changes in various processes, including signaling pathways and gene expression. Efforts to identify components of these responses increasingly depend on mRNA profiling and genetic library screens, yet the functional roles of the genes identified by these assays often remain enigmatic. By comparing the results of these two assays across various cellular responses, we found that they are consistently distinct. Moreover, genetic screens tend to identify response regulators, while mRNA profiling frequently detects metabolic responses. We developed an integrative approach that bridges the gap between these data using known molecular interactions, thus highlighting major response pathways. We harnessed this approach to reveal cellular pathways related to alpha-synuclein, a small lipid-binding protein implicated in several neurodegenerative disorders including Parkinson disease. For this we screened an established yeast model for alphasynuclein toxicity to identify genes that when overexpressed alter cellular survival. Application of our algorithm to these data and data from mRNA profiling provided functional explanations for many of these genes and revealed novel relations between alpha-synuclein toxicity and basic cellular pathways.Cells live in a dynamic environment in which they confront various perturbations such as sudden environmental changes, toxins, and mutations. The response to such perturbations is #To whom correspondence should be addressed. E-mail: lindquist_admin@wi.mit.edu (S. L.); fraenkel-admin@mit.edu (E.F.). 7 Present Address: Department of Cell and Developmental Biology, The University of Pennsylvania, Philadelphia, PA, USA 8 Present Address: Medical College of Georgia, Augusta, GA, USA 9 Present Address: Boston Biomedical Research Institute, Watertown, MA, USA. * These authors contributed equally to this work + These authors contributed equally to this work Summary: A novel approach that integrates genetic hits, differentially expressed genes and known molecular interactions reveals a dramatically enhanced view of cellular responses and was used to create the first cellular map of alpha-synuclein toxicity. NIH Public Access Author ManuscriptNat Genet. Author manuscript; available in PMC 2009 September 1. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript typically complex and comprises signaling and metabolic changes, as well as changes in gene expression. Revealing the cellular mechanisms responding to a specific perturbation may unravel its nature, thus illuminating disease mechanisms 1 or a drug's mode of action 2 ,3 , and identify points of intervention with potential therapeutic value 4 .High-throughput experimental techniques including mRNA profiling and genetic screening are commonly used for revealing components of these response pathways because they provide a genome-and proteome-wide view of molecular changes. mRNA profiling experiments rapidly identify genes that are differentially expressed following stimuli. Genetic screening...