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    Designer DNA: JGI Helps Users Blaze New Biosynthetic Pathways
    In a special issue of the journal Synthetic Biology, JGI scientific users share how they’ve worked with the JGI DNA Synthesis Science Program and what they’ve discovered through their collaborations.

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    A genetic element that generates targeted mutations, called diversity-generating retroelements (DGRs), are found in viruses, as well as bacteria and archaea. Most DGRs found in viruses appear to be in their tail fibers. These tail fibers – signified in the cartoon by the blue virus’ downward pointing ‘arms’— allow the virus to attach to one cell type (red), but not the other (purple). DGRs mutate these ‘arms,’ giving the virus opportunities to switch to different prey, like the purple cell. (Courtesy of Blair Paul)
    A Natural Mechanism Can Turbocharge Viral Evolution
    A team has discovered that diversity generating retroelements (DGRs) are not only widespread, but also surprisingly active. In viruses, DGRs appear to generate diversity quickly, allowing these viruses to target new microbial prey.

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    Algae growing in a bioreactor. (Dennis Schroeder, NREL)
    Refining the Process of Identifying Algae Biotechnology Candidates
    Researchers combined expertise at the National Labs to screen, characterize, sequence and then analyze the genomes and multi-omics datasets for algae that can be used for large-scale production of biofuels and bioproducts.

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    This data image shows the monthly average sea surface temperature for May 2015. Between 2013 and 2016, a large mass of unusually warm ocean water--nicknamed the blob--dominated the North Pacific, indicated here by red, pink, and yellow colors signifying temperatures as much as three degrees Celsius (five degrees Fahrenheit) higher than average. Data are from the NASA Multi-scale Ultra-high Resolution Sea Surface Temperature (MUR SST) Analysis product. (Courtesy NASA Physical Oceanography Distributed Active Archive Center)
    When “The Blob” Made It Hotter Under the Water
    Researchers tracked the impact of a large-scale heatwave event in the ocean known as “The Blob” as part of an approved proposal through the Community Science Program.

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    A plantation of poplar trees. (David Gilbert)
    Genome Insider podcast: THE Bioenergy Tree
    The US Department of Energy’s favorite tree is poplar. In this episode, hear from ORNL scientists who have uncovered remarkable genetic secrets that bring us closer to making poplar an economical and sustainable source of energy and materials.

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    Ian Rambo, graduate student at UT-Austin, was a DOE Graduate Student Research Fellow at the JGI
    Virus-Microbe Interactions of Mud Island Mangroves
    Through the DOE Office of Science Graduate Student Research (SCGSR) program, Ian Rambo worked on part of his dissertation at the JGI. The chapter focuses on how viruses influence carbon cycling in coastal mangroves.

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    HPCwire Editor's Choice Award (logo crop) for Best Use of HPC in the Life Sciences
    JGI Part of Berkeley Lab Team Awarded Best Use of HPC in Life Sciences
    The HPCwire Editors Choice Award for Best Use of HPC in Life Sciences went to the Berkeley Lab team comprised of JGI and ExaBiome Project team, supported by the DOE Exascale Computing Project for MetaHipMer, an end-to-end genome assembler that supports “an unprecedented assembly of environmental microbiomes.”

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    With a common set of "baseline metadata," JGI users can more easily access public data sets. (Steve Wilson)
    A User-Centered Approach to Accessing JGI Data
    Reflecting a structural shift in data access, the JGI Data Portal offers a way for users to more easily access public data sets through a common set of metadata.

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    Phytozome portal collage
    A More Intuitive Phytozome Interface
    Phytozome v13 now hosts upwards of 250 plant genomes and provides users with the genome browsers, gene pages, search, BLAST and BioMart data warehouse interfaces they have come to rely on, with a more intuitive interface.

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    screencap from Amundson and Wilkins subsurface microbiome video
    Digging into Microbial Ecosystems Deep Underground
    JGI users and microbiome researchers at Colorado State University have many questions about the microbial communities deep underground, including the role viral infection may play in other natural ecosystems.

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    Yeast strains engineered for the biochemical conversion of glucose to value-added products are limited in chemical output due to growth and viability constraints. Cell extracts provide an alternative format for chemical synthesis in the absence of cell growth by isolating the soluble components of lysed cells. By separating the production of enzymes (during growth) and the biochemical production process (in cell-free reactions), this framework enables biosynthesis of diverse chemical products at volumetric productivities greater than the source strains. (Blake Rasor)
    Boosting Small Molecule Production in Super “Soup”
    Researchers supported through the Emerging Technologies Opportunity Program describe a two-pronged approach that starts with engineered yeast cells but then moves out of the cell structure into a cell-free system.

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    These bright green spots are fluorescently labelled bacteria from soil collected from the surface of plant roots. For reference, the scale bar at bottom right is 10 micrometers long. (Rhona Stuart)
    A Powerful Technique to Study Microbes, Now Easier
    In JGI's Genome Insider podcast: LLNL biologist Jennifer Pett-Ridge collaborated with JGI scientists through the Emerging Technologies Opportunity Program to semi-automate experiments that measure microbial activity in soil.

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    In their approved proposal, Frederick Colwell of Oregon State University and colleagues are interested in the microbial communities that live on Alaska’s glacially dominated Copper River Delta. They’re looking at how the microbes in these high latitude wetlands, such as the Copper River Delta wetland pond shown here, cycle carbon. (Courtesy of Rick Colwell)
    Monitoring Inter-Organism Interactions Within Ecosystems
    Many of the proposals approved through JGI's annual Community Science Program call focus on harnessing genomics to developing sustainable resources for biofuels and bioproducts.

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    Coloring the water, the algae Phaeocystis blooms off the side of the sampling vessel, Polarstern, in the temperate region of the North Atlantic. (Katrin Schmidt)
    Climate Change Threatens Base of Polar Oceans’ Bountiful Food Webs
    As warm-adapted microbes edge polewards, they’d oust resident tiny algae. It's a trend that threatens to destabilize the delicate marine food web and change the oceans as we know them.

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    Integrating JGI Capabilities for Exploring Earth’s Secondary Metabolome
    Natural Prodcast podcast: Nigel Mouncey
    JGI Director Nigel Mouncey has a vision to build out an integrative genomics approach to looking at the interactions of organisms and environments. He also sees secondary metabolism analysis and research as a driver for novel technologies that can serve all JGI users.

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Home › Our Science › Science Programs & Platforms Leads › Zhong Wang

Zhong Wang

Zhong Wang

Zhong Wang, DOE Joint Genome Institute

Research in the Analysis R&D group focuses on developing new bioinformatics solutions to support JGI in adopting new genomics technologies, scaling up genomics analysis to peta-bases, and enabling data-driven science. This is a group of computational biologists, bioinformaticians, computer scientists and biostatisticians. Through collaborations with internal and external scientists, the Wang group has developed customized data analyses and software to enable “grand-scale” scientific projects. These solutions include large-scale genome variants analyses, next-generation transcriptome de novo assembly, metagenome and metatranscriptome assembly, Hadoop based on sequence analysis framework, etc. For example, this group was responsible for the tera-base scale data analysis in the cow rumen and sheep rumen metagenome projects.

Standing at the intersection between the rapid development of genome and computational technologies, in the coming years the Wang group will continue its effort to explore new genome and computational technologies (NanoPore, GPU, Cloud etc) and their applications in solving DOE’s most challenging problems.

Education

  • PhD Cell Biology. Duke University
  • MS Developmental Biology, Chinese Academy of Sciences, Shanghai, China
  • BS Microbiology, Shandong University, Ji’nan, China

Software

  • ALE, assembly quality evaluation software based on Bayesian statistics
  • BioPig, a Hadoop-based data analytic framework
  • MetaBAT, an automatic metagenome binning software
  • Selected Publications

    1. Weibing Shi, Christina Moon, Sinead Leahy, Dongwan Kang, Jeff Froula, Sandra Kittelmann, Christina Fan, Samuel Deutsch, Dragana Gagic, Henning Seedorf, William Kelly, Renee Atua, Carrie Sang, Priya Soni, Dong Li, Cesar Pinares-Patiño, John McEwan, Peter Janssen, Feng Chen, Axel Visel, Zhong Wang, Graeme Attwood, Edward Rubin. Methane yield phenotypes linked to differential gene expression in the sheep rumen microbiome Genome Research (2014). gr. 168245.113
    2. Jeffrey A. Martin, Nicole V. Johnson, Stephen M. Gross, James Schnable, Xiandong Meng, Mei Wang, Devin Coleman-Derr, Erika Lindquist, Chia-Lin Wei, Shawn Kaeppler, Feng Chen, and Zhong Wang. A near complete snapshot of the Zea mays seedling transcriptome revealed from ultra-deep sequencing. Scientific Reports (2014). DOI: 10.1038/srep04519.
    3. Byrne RT, Klingele AJ, Cabot EL, Schackwitz WS, Martin JM, Martin J, Wang Z, Wood EA, Pennacchio C, Pennacchio LA, Perna NT, Battista JR, and Cox MM. Evolution of Extreme Resistance to Ionizing Radiation via Genetic Adaptation of DNA Repair. eLife (2014). In press.
    4. Nordberg H, Bhatia K, Wang K, Wang Z. BioPig: A Hadoop-based Analytic Toolkit for Large-Scale Sequence Data. Bioinformatics (2013). doi:10.1093/bioinformatics/btt528
    5. Scott Clark, Rob Egan, Peter I. Frazier, and Zhong Wang. ALE: a Generic Assembly Likelihood Evaluation Framework for Assessing the Accuracy of Genome and Metagenome Assemblies. Bioinformatics (2013). doi: 10.1093/bioinformatics/bts723
    6. Koren S, Schatz MC, Walenz BP, Martin J, Howard JT, Ganapathy G, Wang Z, Rasko DA, McCombie WR, Jarvis ED, Phillippy AM. Hybrid error correction and de novo assembly of single-molecule sequencing reads. Nature biotechnology. 2012 Jul 1
    7. Martin J. and Wang Z. Next generation transcriptome assembly. Nature Reviews Genetics. 2011;12(10):671-82.
    8. Hess M, Sczyrba A, Egan R, Kim TW, Chokhawala H, Schroth G, Luo S, Clark DS, Chen F, Zhang T, Mackie RI, Pennacchio LA, Tringe SG, Visel A, Woyke T, Wang Z, Rubin EM. Metagenomic discovery of biomass-degrading genes and genomes from cow rumen. Science. 2011 Jan 28;331(6016):463-7
    9. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics. 2009 Jan;10(1):57-63
    10. Nagalakshmi U, Wang Z(co-first), Waern K, Shou C, Raha D, Gerstein M, Snyder M. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science. 2008 Jun 6;320(5881):1344-9
    11. Wang Z, Willard HF, Mukherjee S, Furey TS. Evidence of influence of genomic DNA sequence on human X chromosome inactivation. PLoS Computational Biology. 2006 Sep 1;2(9):e113
    12. Wang Z, Lin H. Nanos maintains germline stem cell self-renewal by preventing differentiation. Science. 2004 Mar 26;303(5666):2016-9
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