HPC Unlocks Secret to Drought-Resistant Crops

April 20, 2017

This network shows the cross-species co-expression relationships between genes in Arabidopsis and Agave. Dark green nodes represent Agave genes, light green nodes represent Arabidopsis genes, blue edges represent positive co-expression relationships, and red edges represent negative co-expression relationships. The co-expression network was used in the paper to investigate the co-expression relationships of genes within the same gene family.

OAK RIDGE, Tenn., April 20, 2017 — A multi-institution research team has used supercomputing to understand processes leading to increased drought resistance in food and fuel crops.

Photosynthesis, the method plants use to convert energy from the sun into food, is a ubiquitous process many people learn about in elementary school. Almost all plants use photosynthesis to gather energy and stay alive.

Not all photosynthetic processes are the same, though. In recent years, researchers have grown increasingly interested in desert plants’ preferred method of photosynthesis—crassulacean acid metabolism (CAM), a process named after the Crassulaceae family of plants, which include succulents like friendship plants, pig’s ears, and hens and chicks.

These plants caught researchers’ attention because of their seemingly opposite photosynthetic schedule, and understanding this process may be the genetic key to helping plants of all kinds conserve water. With a more fundamental understanding of CAM, scientists aim to help the plants upon which society relies for food and fuel become more drought resistant, thereby expanding the area where crops can grow and thrive.

“One of the benefits of CAM photosynthesis is water efficiency,” said Oak Ridge National Laboratory (ORNL) computational biologist Dan Jacobson, who is part of a multi-institutional team that recently published a CAM study in Nature Plants. “When you think of bioenergy and food crops, you want them to be able to tolerate drought stress or grow in areas that aren’t currently arable land. That means they have to be able to withstand some kind of environmental stress, most commonly drought stress. CAM species are very good at this.”

To that end, Jacobson works with a large group of experimentalists and computational scientists to more fully understand the CAM process. This cross-omics team (combining expertise in metabolomics, proteomics, and genomics) uses computing resources at the Oak Ridge Leadership Computing Facility (OLCF)—a US Department of Energy Office of Science User Facility located at ORNL—to catalog how plants’ CAM processes vary and ultimately uncover how CAM processes may be genetically engineered into feed stock, food crops, and crops for bioenergy applications.

Shining a light on photosynthesis

When most people think of photosynthesis, they are actually thinking of a specific form, called C3 photosynthesis. This process follows the Calvin Cycle, in which plants capture light energy during the day and convert it into energy-bearing adenosine triphosphate (ATP).

ATP helps plants split water atoms into their hydrogen and oxygen constituent particles. Meanwhile, a C3 photosynthetic plant opens up small pores—called stomata—to absorb carbon dioxide from the atmosphere. Then at night, the newly freed hydrogen particles combine with carbon dioxide absorbed during the day to create the carbohydrates plants use to live and grow.

CAM photosynthesis works the same way, but stomata open for respiration at night and stay tightly closed during the day, allowing plants to conserve more water. This helps plants like cactus and Agave survive in climates where water is scarce.

Less than 10 percent of known plant species use this specialized form of photosynthesis, but researchers hope that by understanding how CAM works, they can apply this water-saving method to other plants. To do that, though, researchers need to understand how molecules interact during CAM photosynthesis and how metabolites and proteins change over time.

Data-intensive design

In addition to simulating processes too dangerous or complex for experiments, supercomputers also help scientists make connections in vast amounts of data. For this project, researchers from ORNL, the University of Tennessee, Newcastle University in the United Kingdom, and the University of Nevada, Reno gathered photosynthesis data from Agave (a CAM plant) and compared it with the Arabidopsis genus of plants (C3 plants). To conduct a study between Agave and a C3 plant, the team selected the Arabidopsis genus plant thale cress, one of the first plants to have its genome sequenced and a good candidate for plant studies.

The team then studied what gene expressions control stomata opening and closing in both CAM and C3 plants and how proteins regulated this process. Collecting this data in both a common CAM and a C3 species allowed the team to distinguish traits ubiquitous to CAM plants from species-specific traits. However, finding these connections required a machine capable of comparing large data sets against themselves.

Jacobson and his collaborators used the OLCF’s Eos analysis cluster to run “all-versus-all” comparisons of the team’s data sets. These comparisons scan large data sets and compare each individual plant’s data with all others. This helps the team form relationships between the metabolic processes underpinning CAM in individual Agave specimens as well as the differences between Agave’s CAM properties from thale cress’s C3 properties.

“These all-against-all vector comparisons for correlation networks allowed us to look for different types of patterns and different times of day where the [gene expression] transcripts are correlated with each other, where they were correlated to proteins or metabolites, or times of the day where they shift dramatically,” Jacobson said.

The team members gained access to OLCF resources through the OLCF’s Director’s Discretionary program, and after familiarizing themselves with Titan’s hybrid architecture, they plan to expand research into other CAM species, comparing larger data sets and more fully cataloging CAM processes. “As we gain more knowledge from these various approaches, we hope to tease apart the underlying mechanisms for CAM and how it is regulated,” Jacobson said. “That starts to build toward having enough knowledge to deploy CAM in a new species.”

Jacobson also indicated that without access to high-performance computing, the team would not have been able to find these meaningful connections in a timely manner. “This is the first study looking at a cross-omics, time-course experiment to try and explore CAM at this molecular detail,” he said. “I think the ability to use supercomputing infrastructure enabled things that wouldn’t have been possible otherwise. We were able to have a pretty big impact on the analysis of this work because of those resources.”

Related Publication: P. Abraham, H. Yin, A. Borland, D. Weighill, et al., “Transcript, Protein, and Metabolite Temporal Dynamics in the CAM Plant Agave.” Nature Plants 12, no. 2 (2016): 1–10, doi:10.1038/nplants.2016.178.

About Oak Ridge National Laboratory

Oak Ridge National Laboratory is supported by the US Department of Energy’s Office of Science. The single largest supporter of basic research in the physical sciences in the United States, the Office of Science is working to address some of the most pressing challenges of our time. For more information, please visit science.energy.gov.


Source: ORNL

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

TACC Helps ROSIE Bioscience Gateway Expand its Impact

April 26, 2017

Biomolecule structure prediction has long been challenging not least because the relevant software and workflows often require high-end HPC systems that many bioscience researchers lack easy access to. Read more…

By John Russell

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

IBM, Nvidia, Stone Ridge Claim Gas & Oil Simulation Record

April 25, 2017

IBM, Nvidia, and Stone Ridge Technology today reported setting the performance record for a “billion cell” oil and gas reservoir simulation. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of “quantum supremacy,” researchers are stretching the limits of today’s most advanced supercomputers. Read more…

By Tiffany Trader

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference phase of neural networks (NN). Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the campaign. Read more…

By John Russell

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its assets. Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. Read more…

By John Russell

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This