PPubMed20 Mar 2017Cited 164×

TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network

Matej Usaj, Yizhao Tan, Wen Wang, Benjamin VanderSluis, Albert Zou, Chad L. Myers, Michael Costanzo, Brenda Andrews, Charles Boone

Abstract

'Chad L. Myers' 'Michael Costanzo' 'Brenda Andrews' 'Charles Boone'] Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae. In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner.

A figure from TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network — fig. from the paper

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TheCellMap.org provides an online database and tools to explore a global yeast genetic interaction network derived from millions of SGA experiments.

What’s new

i.Developed TheCellMap.org, a web‑accessible database for yeast genetic interaction data.
ii.Integrated quantitative data from ~23 million double‑mutant SGA screens, covering ~550 k negative and ~350 k positive interactions.
iii.Implemented interactive visualizations of global and gene‑specific interaction‑profile similarity networks.
iv.Analyzed neighboring gene effects, identifying 392 genes (<7 % of tested) potentially affected.
v.Provided downloadable datasets and tools for network annotation and custom analysis.

How they did it

The authors performed genome‑scale Synthetic Genetic Array (SGA) experiments to generate ~23 million yeast double‑mutant strains and measured fitness to quantify genetic interactions. Data were stored in a PostgreSQL database and served through a Python/Django backend, with network layouts generated using edge‑weighted spring‑embedded algorithms and visualized via HTML5/JavaScript.

What they found

~23 million double‑mutant strains analyzed, yielding ~550,000 negative and ~350,000 positive genetic interactions.
Global profile‑similarity network contains 4,909 nodes (4,418 unique genes) and 34,468 edges (PCC ≥ 0.2).
569 GO bioprocess terms significantly enriched, defining 19 network regions covering 1,480 genes.
Identified 392 genes (<7 % of all tested) with potential neighboring‑gene effects (PCC > 0.1, distance < 400 bp).

Caveats

✕The analysis is limited to interactions detectable by SGA screens and may miss weaker or condition‑specific interactions.
✕Neighboring‑gene effect assessment uses conservative thresholds, possibly underestimating its prevalence.
✕The current network relies on a PCC ≥ 0.2 cutoff, which excludes lower‑similarity relationships.
✕The database currently contains data for S. cerevisiae only and does not include other organisms.

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