Broadening horizons: holistic viewpoints from the Biology of Genomes

A report on the Cold Spring Harbor Laboratory 27th annual meeting on the Biology of Genomes, held in Cold Spring Harbor, New York, USA, 6-10 May 2014

Genotype-Environment Interactions Reveal Causal Pathways That Mediate Genetic Effects on Phenotype

Unraveling the molecular processes that lead from genotype to phenotype is crucial for the understanding and effective treatment of genetic diseases. Knowledge of the causative genetic defect most often does not enable treatment; therefore, causal intermediates between genotype and phenotype constitute valuable candidates for molecular intervention points that can be therapeutically targeted. Mapping genetic determinants of gene expression levels (also known as expression quantitative trait loci or eQTL studies) is frequently used for this purpose, yet distinguishing causation from correlation remains a significant challenge. Here, we address this challenge using extensive, multi-environment gene expression and fitness profiling of hundreds of genetically diverse yeast strains, in order to identify truly causal intermediate genes that condition fitness in a given environment. Using functional genomics assays, we show that the predictive power of eQTL studies for inferring causal intermediate genes is poor unless performed across multiple environments. Surprisingly, although the effects of genotype on fitness depended strongly on environment, causal intermediates could be most reliably predicted from genetic effects on expression present in all environments. Our results indicate a mechanism explaining this apparent paradox, whereby immediate molecular consequences of genetic variation are shared across environments, and environment-dependent phenotypic effects result from downstream integration of environmental signals. We developed a statistical model to predict causal intermediates that leverages this insight, yielding over 400 transcripts, for the majority of which we experimentally validated their role in conditioning fitness. Our findings have implications for the design and analysis of clinical omics studies aimed at discovering personalized targets for molecular intervention, suggesting that inferring causation in a single cellular context can benefit from molecular profiling in multiple contexts

Harnessing gene expression to identify the genetic basis of drug resistance

The advent of cost-effective genotyping and sequencing methods have recently made it possible to ask questions that address the genetic basis of phenotypic diversity and how natural variants interact with the environment. We developed Camelot (CAusal Modelling with Expression Linkage for cOmplex Traits), a statistical method that integrates genotype, gene expression and phenotype data to automatically build models that both predict complex quantitative phenotypes and identify genes that actively influence these traits. Camelot integrates genotype and gene expression data, both generated under a reference condition, to predict the response to entirely different conditions. We systematically applied our algorithm to data generated from a collection of yeast segregants, using genotype and gene expression data generated under drug-free conditions to predict the response to 94 drugs and experimentally confirmed 14 novel gene–drug interactions. Our approach is robust, applicable to other phenotypes and species, and has potential for applications in personalized medicine, for example, in predicting how an individual will respond to a previously unseen drug

Environmental Stresses Disrupt Telomere Length Homeostasis

Telomeres protect the chromosome ends from degradation and play crucial roles in cellular aging and disease. Recent studies have additionally found a correlation between psychological stress, telomere length, and health outcome in humans. However, studies have not yet explored the causal relationship between stress and telomere length, or the molecular mechanisms underlying that relationship. Using yeast as a model organism, we show that stresses may have very different outcomes: alcohol and acetic acid elongate telomeres, whereas caffeine and high temperatures shorten telomeres. Additional treatments, such as oxidative stress, show no effect. By combining genome-wide expression measurements with a systematic genetic screen, we identify the Rap1/Rif1 pathway as the central mediator of the telomeric response to environmental signals. These results demonstrate that telomere length can be manipulated, and that a carefully regulated homeostasis may become markedly deregulated in opposing directions in response to different environmental cues

An Immune Atlas of Clear Cell Renal Cell Carcinoma

Immune cells in the tumor microenvironment modulate cancer progression and are attractive therapeutic targets. Macrophages and T cells are key components of the microenvironment, yet their phenotypes and relationships in this ecosystem and to clinical outcomes are ill defined. We used mass cytometry with extensive antibody panels to perform in-depth immune profiling of samples from 73 clear cell renal cell carcinoma (ccRCC) patients and five healthy controls. In 3.5 million measured cells, we identified 17 tumor-associated macrophage phenotypes, 22 T cell phenotypes, and a distinct immune composition correlated with progression-free survival, thereby presenting an in-depth human atlas of the immune tumor microenvironment in this disease. This study revealed potential biomarkers and targets for immunotherapy development and validated tools that can be used for immune profiling of other tumor types.ISSN:0092-8674ISSN:1097-417

Measuring Signaling and RNA-Seq in the Same Cell Links Gene Expression to Dynamic Patterns of NF-κB Activation

Signaling proteins display remarkable cell-to-cell heterogeneity in their dynamic responses to stimuli, but the consequences of this heterogeneity remain largely unknown. For instance, the contribution of the dynamics of the innate immune transcription factor nuclear factor κB (NF-κB) to gene expression output is disputed. Here we explore these questions by integrating live-cell imaging approaches with single-cell sequencing technologies. We used this approach to measure both the dynamics of lipopolysaccharide-induced NF-κB activation and the global transcriptional response in the same individual cell. Our results identify multiple, distinct cytokine expression patterns that are correlated with NF-κB activation dynamics, establishing a functional role for NF-κB dynamics in determining cellular phenotypes. Applications of this approach to other model systems and single-cell sequencing technologies have significant potential for discovery, as it is now possible to trace cellular behavior from the initial stimulus, through the signaling pathways, down to genome-wide changes in gene expression, all inside of a single cell