/
2012 01 17 TSW at PAG

2012 01 17 TSW at PAG

Jan 23, 2012

Abstracts for General iPlant Workshop

Eric Lyons - Introduction to iPlant's Cyberinfrastructure

University of Arizona -- elyons.uoa@gmail.com

The iPlant Collaborative’s mission is to create a comprehensive set of cyberinfrastructure to support plant research.  Concluding year four of this project, iPlant has successfully developed and deployed a variety of integrated technologies and computational resources that provide access to large data storage, high-performance computing, grid computing, and cloud computing.  These resources are made assessable to a diversity of scientists including field biologists, experimental biologists, computational biologists and computer scientists by providing access at multiple levels including application programming interfaces (APIs), RESTful services, and a variety of rich web-based systems to access data, integrate computational tools, and perform analyses.  This workshop will give an overview of iPlant’s computational resources, how a set of plant biologists have made use of these technologies to enable their research through scalable computation and how they have enabled others to use their methodologies, and provide a hands-on training session on how to use a subset of iPlant’s resources including:

Haibao Tang - Leverage iPlant computing resources for collaborative genomic research

J. Craig Venter Institute -- tanghaibao@gmail.com

The ability to sequence novel genomes using high-throughput methods has tremendously enabled the decoding of biological information to many research labs and investigators. The “democratization” of sequencing notwithstanding, the processing and data mining of the large amounts of sequences require massive computing and storage resources and technical know-hows. The iPlant collaborative has built a dedicated platform to distribute these resources to a wide range of researchers, small labs and large genome centers alike. With the help of iPlant and Texas Advanced Computing Center (TACC) staffs, we now have access to many more high-RAM servers and computing farms for the rapid production of large genome assemblies and annotations. We have compiled the Celera Assembler (CA) and MAKER pipelines as VMs that can be run on Atmosphere – the iPlant’s cloud computing solution. The Atmosphere images provide unique mechanism to quickly distribute working pipelines for common analyses tasks, such as genome assembly and annotation, which are relatively difficult for small labs to install and configure. Through connections to other researchers facing similar problems, iPlant connects researchers on the “social” level and greatly enhance the experience of sharing of methodology and data. Additionally, we believe that genome centers, such as JCVI, need to take more active role in working with iPlant to transfer the technical know-hows into an open cloud-based domain and gradually move away from the institutional legacy systems which are less transparent and un-sustainable in the long run.

Steven Eichten - Contribution of epigenetic variation to expression changes among tissues and genotypes.

University of Minnesota -- eicht021@umn.edu

Epigenetic variation describes heritable differences that are not attributable to changes in DNA sequence. In particular, epigenetic information can affect the transcription level for genes and thereby influence phenotype. Methylation of cytosine residues provides one mechanism for the inheritance of epigenetic information. Genome-wide methylation patterns were profiled in several tissues of the maize inbreds B73 and Mo17 using methylated DNA immunoprecipitation followed by hybridization to custom designed microarrays (meDIP-chip). The gene expression levels in the same tissues were assessed using RNAseq. There are numerous examples of differential methylation between the two genotypes including a subset that correlate with altered expression of nearby genes. However, with the exception of endosperm tissue there are relatively few differences of altered DNA methylation patterns in maize tissues. An expansion of this work will integrate large-scale sequence-based analysis of epigenetic and transcriptional variation across a wide number of diverse maize lines to assess the role of epigenetics in natural phenotypic variation.

Nathan Miller - Enabling phenotypic image analysis using shared cyberinfrastructure

University of Wisconsin -- ndmill@gmail.com

Understanding how an organism's genotype and environment influence its growth, development and physiology requires an array of genetic and phenotyping tools. While many genetic resources exist including high-throughput sequencing methods, t-DNA insertion lines, gene micro-arrays, and structured genomic populations for statistical genomic studies, there are relatively few high-throughput  methods for monitoring and modeling dynamic and complex phenotypes. Presented here is an example of image processing methods applied to analyzing root gravitropism. High-spatiotemporal (5 ?m/pixel and 2 min/frame) imaging of root gravitropism can be automatically analyzed via machine vision technologies and phenotypic features extracted including growth rate, tip angle, and curvature. These data-rich phenotypes can be combined with tensor algebra to produce data models which can succinctly describe a complex process with a small set of biologically relevant numbers. Making the phenotypic image analysis tools available as a shared resource can enable the plant community to more quickly make detailed phenotypic measurements. iPlant's cyber-infrastructure is a flexible platform able to deploy and house these computational methods as a shared community resource.  Currently, a growing community is leveraging these tools for phenotypic assay's and educational purposes.

Sheldon McKay - iPlant's Software and Cyberinfrastructure for Your Research (70 minutes hands-on)

DNA Learning Center, Cold Spring Harbor Laboratory -- mckays@cshl.edu

The iPlant Discovery Environment (DE) is a system for managing and running tools, analyses, and workflows. The DE connects various components of iPlant's cyberinfrastructure together to create a rich web-based system for analyzing data. The DE contains a growing list of integrated applications for scientific workflows and a mechanism for users to integrate their own applications.

In this hands-on session, we will demonstrate how to use the DE by guiding users through an RNA-seq workflow. RNA-seq refers to whole transcriptome shotgun sequencing of cDNA, generally using an ultra-high-throughput ("next-generation") sequencing technology. The value of RNAseq is the ability generate deep-coverage information about a sample's RNA. This can be used for a variety of purposes such as transcriptome assembly, gene discovery/annotation, and detecting differential transcript abundances between tissues, developmental stages, genetic backgrounds, and environmental conditions. In this example we will compare gene transcript abundance between wild type and mutant Arabidopsis strains.

Presentations:

Eric Lyons:

Steven Eichten:

Nate Miller:

Haibao Tang: