A comprehensive enhancer screen identifies TRAM2 as a key and novel mediator of YAP oncogenesis

Background: Frequent activation of the co-transcriptional factor YAP is observed in a large number of solid tumors. Activated YAP associates with enhancer loci via TEAD4-DNA-binding protein and stimulates cancer aggressiveness. Although thousands of YAP/TEAD4 binding-sites are annotated, their functional importance is unknown. Here, we aim at further identification of enhancer elements that are required for YAP functions. Results: We first apply genome-wide ChIP profiling of YAP to systematically identify enhancers that are bound by YAP/TEAD4. Next, we implement a genetic approach to uncover functions of YAP/TEAD4-associated enhancers, demonstrate its robustness, and use it to reveal a network of enhancers required for YAP-mediated proliferation. We focus on EnhancerTRAM2, as its target gene TRAM2 shows the strongest expression-correlation with YAP activity in nearly all tumor types. Interestingly, TRAM2 phenocopi

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

A Multi-objective Floorplanner for Shuttle Mask Optimization

Shrinkage of VLSI feature size and use of advanced Reticle Enhancement Technologies (RET) in manufacturing such as OPC and PSM have dramatically pushed up cost of mask. For example of a 130nm or 90nm mask set, the mask cost can easily reach one or two million US dollars. Shuttle mask is an effective method to share the mask cost by putting different chips on the same mask. Shuttle mask floorplanning is a key step to pack these chips according to certain objectives and constraints related to cost, yield, and manufacturability. In this paper, we present a simulated annealing based floorplanner to solve the shuttle mask floorplanning problem with multiple optimization objectives and constraints. We will consider area minimization, density optimization (for manufacturability enhancement with CMP), wafer utilization maximization, die-to-die inspection constraint, die orientation constraint and their combinations. A nice property of our floorplanner is that it can be easily adapted to different cost models of mask and wafer manufacturing. Experiments on industry data show promising results