Difference between revisions of "EPIC-CoGe"

Revision as of 13:55, 29 July 2013

http://www.plant-epigenome.org/

Funding for the EPIC-CoGe Browser Project is provided by: The Gordon and Betty Moore Foundation

Demo Videos and Screenshots

Try EPIC-CoGe

Here is EPIC-CoGe set to Browser the genome of Arabidopsis thaliana with over 700 epigenomic experiments loaded: http://genomevolution.org/CoGe/GenomeView.pl?gid=16911&viewer=JBrowse

Video

Screenshots

Try EPIC-CoGe: http://genomevolution.org/r/939v . Beta version of quantitative visualization using CoGe's new genome browser based on JBrowse

Prototype version of quantitative visualization using CoGe's genome browser based on OpenLayers

Brief Overview

This project will develop an extension to CoGe to:

• Store epigenetic data for Arabidopsis
• Provide dynamic visualization through CoGe's Genome Viewer
• Provide data management tools for organizing epigenetic data

Tutorial

The EPIC-CoGe Browser is ready for beta testing. This EPIC-CoGe Tutorial will get you started.

Long-term vision

• Once developed for Arabidopsis, extend to all other genomes in CoGe
• Permit users to upload their own data, keep it private, share with collaborators, and make public upon publication
• Expand data storage engine to include all types of quantitative genomic data including
  • Expression profiles
  • RNASeq
  • Copy number variation
  • SNPs
  • QTLs

Summary

How eukaryotic organisms regulate mRNA levels is a fundamental question in biology. Most of the early attention was focused on the study of gene transcription, while only recently posttranscriptional mechanisms have gained recognition for their regulatory importance. These epigenetic regulatory pathways control mRNA levels both transcriptionally and posttranscriptionally, and pioneering work in Arabidopsis thaliana has helped define these processes. For this reason, there is a wealth of epigenomic information already available for this model plant. However, it is almost entirely unusable to the wider research community due to the computational intensive procedures needed to leverage these data resources. For this reason, we will develop an easy to use web-based system to store, access, and visualize Arabidopsis epigenetic data in a comparative genomics context: the EPIC-CoGe Browser.

The EPIC-CoGe Browser will consist of four major subsystems:

• A data storage subsystem that can store thousands of epigenetic experiments and provide rapid access to those data.
• A web-based visualization subsystem that permits overlaying and partitioning of epigenetics data on genomic data.
• A user interface subsystem to allow researchers to find and select sets of epigenetic experiments for visualization.
• A user interface subsystem to allow researchers to customize how to mesh and visualize their selected epigenetics experiments.

The EPIC-CoGe Browser will synthesize existing investments from three NSF funded projects: EPIC, CoGe, and the iPlant Collaborative. EPIC, whose mission is “reading the second [genetic] code [of life by] mapping epigenomes to understand plant growth, development and adaptation to the environment,” is currently funded as a Research Coordination Network. Their primary goal has been to coordinate the research activities of the international community and develop a whitepaper to drive this effort. However, this community currently lacks a computational browser to access and visualize epigenetic data. Also, their research interests are diverse. While much of the epigenetic community originally focused on the model plant system, Arabidopsis thaliana, the community research interests span all plants, including those of agronomic importance for global food safety and sustainability. However, to achieve such broad applicability, the EPIC-CoGe Browser requires scalable computing resources and data management systems.

The iPlant Collaborative is a large investment by the NSF to create cyberinfrastructure (CI) for the plant research community. Cyberinfrastructure is made up of extensible, scalable, and capable computing resources, and “domain expertise”, which includes computer science, mathematics, statistics, algorithms, and all disciplines of plant biology. iPlant is building and deploying the software systems necessary to connect supercomputing resources (XSEDE) to computational biologists, bench biologists, field biologists, and plant breeders. The comparative genomics platform, CoGe, is part of the “powered by iPlant” program. CoGe utilizes iPlant’s CI in order to achieve the scalability necessary to serve the entire comparative genomics community for all domains of life (CoGe currently makes available 16,500 genomes from ~13,000 organisms). In addition, CoGe provides a suite of web-based tools for in-depth analyses and comparisons of genomic data. The EPIC-CoGe Browser will be an extension of CoGe and likewise a member of the Powered by iPlant program to access the required scalable and capable computational resources.

While year one of this project will focus on public epigenetics data for Arabidopsis thaliana and developing the four subsystems described above, as the technology continues to improve for amassing epigenetics data easily and inexpensively, the need for the EPIC-CoGe Browser will continue to grow as more plant species are investigated. Year two of the project will focus on catering to the needs of the epigenetic research community by: 1. providing researchers with more data management and collaboration tools, 2. supporting additional organisms, and 3. supporting advanced comparative analyses and publication quality images. Data management and collaboration tools are required for on-going research with pre-publication data. These systems will permit researchers to add their own data to EPIC-CoGe, share those data among a group of researchers, and restrict their public access, while also being able to engage the broader community for soliciting help and analytical expertise. EPIC-CoGe will engage the rice and maize research communities in order to expand EPIC-CoGe Browser’s capabilities into additional species, and specifically those with agronomic and food safety importance. By being based on the CoGe system, which inherently supports thousands of organisms, these examples will permit the expansion of EPIC-CoGe to all domains of life. In addition, CoGe provides many tools for comparative genomics, and the data visualizations of EPIC-CoGe will be adapted for use in these tools. This synthesis of data and analytical tools will permit information from well-studied plants to be leveraged for less understood plants.

In order to best meet the needs of the plant epigenetic research community, year two will also focus on soliciting feedback from scientists through online questionnaires, discussion forums, and workshops. The workshops will be held at national and international conferences that the Co-PIs regularly attend: Gregory at the International Conference on Arabidopsis Research, and Lyons at the Annual Maize Genetics Conference.

By leveraging these resources provided by the NSF, the support of the Betty and Gordon Moore Foundation for the first two years of the EPIC-CoGe Browser development will create the synergistic glue required to make epigenetic data available to the widest group of international researchers. Such support will be leveraged for the long-term viability of all three projects through new funding opportunities from domestic, international, and industrial partnerships. Currently, Co-PIs Lyons and Gregory have a proposal with the NSF Plant Genome Research Program to provide support for this project starting in year three and focused on rice epigentic data. In addition, a functional prototype EPIC-CoGe Browser has been deployed: http://genomevolution.org/CoGe/GenomeView.pl?gid=16911&viewer=JBrowse

Please note that this is a prototype system that will improve over time. If you have any feedback, please email the CoGe Team.

Support from GBMF will ensure the completion of the goals outlined above and provide much needed resources for the international epigenetics community.

Support

This web site is funded by the Gordon and Betty Moore Foundation through Grant GBMF3383 to Eric Lyons. This project is a collaboration between the labs of Eric Lyons at the University of Arizona and Brian Gregrory at the University of Pennsylvania.