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    Data yielded from RIViT-seq increased the number of sigma factor-gene pairs confirmed in Streptomyces coelicolor from 209 to 399. Here, grey arrows denote previously known regulation and red arrows are regulation identified by RIViT-seq; orange nodes mark sigma factors while gray nodes mark other genes. (Otani, H., Mouncey, N.J. Nat Commun 13, 3502 (2022). https://doi.org/10.1038/s41467-022-31191-w)
    Streamlining Regulon Identification in Bacteria
    Regulons are a group of genes that can be turned on or off by the same regulatory protein. RIViT-seq technology could speed up associating transcription factors with their target genes.

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    (PXFuel)
    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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    Photograph of a stream of diatoms beneath Arctic sea ice.
    Polar Phytoplankton Need Zinc to Cope with the Cold
    As part of a long-term collaboration with the JGI Algal Program, researchers studying function and activity of phytoplankton genes in polar waters have found that these algae rely on dissolved zinc to photosynthesize.

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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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    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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    A view of the mangroves from which the giant bacteria were sampled in Guadeloupe. (Hugo Bret)
    Giant Bacteria Found in Guadeloupe Mangroves Challenge Traditional Concepts
    Harnessing JGI and Berkeley Lab resources, researchers characterized a giant - 5,000 times bigger than most bacteria - filamentous bacterium discovered in the Caribbean mangroves.

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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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Our Science
Home › Our Science › Science Programs & Platforms Leads › IMG Group

IMG Group

The Integrated Microbial Genomes group is focused on:

  1. Developing state-of-the-art data processing and analysis pipelines for the interpretation of microbiome omics data
  2. Developing forward-looking strategies for the deployment of computational workflows at peta- and exa- scales on multicore and manycore architectures with the ultimate objective of facilitating omics-based scientific investigations.
  3. Development and maintenance of the Integrated Microbial Genomes (IMG) data management system

Overall, the IMG group owns and maintains integral components of JGI’s production workflow, and is responsible for the annotation and analysis of (meta)genomic, (meta)transcriptomic, and functional genomic data and serving them to users via the Integrated Microbial Genomes (IMG) system (https://img.jgi.doe.gov).

Selected ongoing methods developed and related software resources are described below.

 

omics-2Average Nucleotide Identity (ANI)

As part of this project, pairwise average nucleotide identities (ANI) and fraction of orthologous genomic regions (Alignment fraction, AF) have been computed for nearly 28,000 bacterial and archaeal genomes. By clustering genomes based on their pairwise AF and ANI values, we were able to ascertain mis-assignment of species names in genomes spanning nearly 18% of all existing species. Additionally, the complete linkage clustering made it possible to confidently assign species to nearly 326 genomes. Through the analysis of cliques, it has also become possible to identify speciation events within existing species. Within the JGI’s production pipeline, ANI is used to ascertain the species specificity of single cells and genomes extracted from metagenomes, and also as a metric for quality control within IMG. While ANI is integrated within IMG, http://ani.jgi-psf.org serves the current data.

 

 

Integrated Microbial Genomes (IMG)

The mission of the Integrated Microbial Genomes & Microbiomes (IMG/M) system is to support the annotation, analysis and distribution of microbial genome and microbiome datasets sequenced at DOE’s Joint Genome Institute (JGI). IMG/M is also open to scientists worldwide for the annotation, analysis, and distribution of their own genome and microbiome datasets, as long as they agree with the IMG/M data release policy and follow the metadata requirements for integrating data into IMG/M (see IMG/M submission site). The Integrated Microbial Genomes (IMG) system serves as a community resource for analysis and annotation of genome and metagenome datasets in a comprehensive comparative context. The IMG data warehouse integrates genome and metagenome datasets provided by IMG users with a comprehensive set of publicly available genome and metagenome datasets. IMG is a collaboration between the DOE JGI and the Biosciences Computing Group at the Computational Research Division of LBNL.

.

Research Team

Neha Varghese Marcel Huntemann
I-Min (Amy) Chen 
Lead, Computational Infrastructure
Neha Varghese, Software Developer Marcel Huntemann,   Software Developer

Ken Chu

Group Lead, Interface & Data Analysis

 

IMAChen@lbl.gov
(925) 296-5697
njvarghese@lbl.gov
(925) 296-5696
mhuntemann@lbl.gov
(925) 927-2534
KLChu@lbl.gov
(925) 926-5692
Amy is leading the computational infrastructure groups of the Prokaryote Program. She is also leading the technical development of the Integrated Microbial Genomes (IMG) family of systems.

More about Amy here

Neha’s research mainly focuses on the use of genome sequences to delineate prokaryotic organisms. She is also actively involved in expression analysis of transcriptomic and metatranscriptomic data, specifically exploring, benchmarking and implementing user-based RNAseq data analysis tools. Marcel is in charge of several production pipelines (gene calling,
functional annotation and methylomics) that run on microbial genomes
and metagenomes. He also works on automating intra-department data
exchange and assists with large scale computations on R&D projects.
Ken is leading the development and maintenance of analytical tools and user interface components for the IMG family of systems.

 

 

Krishna Palaniappan,

Software Engineer, Database systems

Manoj Pillay, 
Software Engineer, Database systems
Jinghua (Jenny) Huang

Software Engineer, Database analysis

Anna Ratner

Software Engineer, Database analysis

KPalaniappan@lbl.gov
(925) 296-5710
mpillay@lbl.gov
(925) 296-5820
JinghuaHuang@lbl.gov
(925) 926-5827
ARatner@lbl.gov
(925) 296-5823
Krishna is responsible for the design and maintenance of the Integrated Microbial Genomes (IMG) data warehouse, and integration of genomic and metagenomic data with transcriptomics and proteomics data.

More about Krishna here.

Manoj is responsible for integrating omics datasets into the IMG data warehouse, their distribution to users and the acquisition of public data from open-access sequence repositories into IMG.

More about Manoj here

Jenny is working on the display and visualization of large amount isolate genomic and metagenomic data stored in Oracle databases, Berkeley DB and files in various formats.

More about Jenny here

Anna is working on the display and visualization of large omics data.

More about Anna here

Selected Publications

  1. Ovchinnikov S. et al. (2017) Protein structure determination using metagenome sequence data. Science 355(6322):294-298
  2. Paez-Espino D. et al. (2017) IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses. Nucleic Acids Res. 45(D1):D457-D465.Paez-Espino, D. et al. (2016) Uncovering Earth’s virome. Nature 536:425-30
  3. Chen IA. et al. (2017) IMG/M: integrated genome and metagenome comparative data analysis system. Nucleic Acids Res. 45(D1):D507-D516.
  4. Paez-Espino, D. et al. (2016) Uncovering Earth’s virome. Nature 536:425-30
  5. Chen IM. et. al. (2016) Supporting community annotation and user collaboration in the integrated microbial genomes (IMG) system. BMC Genomics. 17:307
  6. Huntemann M. et al. (2016) The standard operating procedure of the DOE-JGI Metagenome Annotation Pipeline (MAP v.4). Stand Genomic Sci. 11:17
  7. Huntemann M. et al. (2015) The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4). Stand Genomic Sci. 10:86.
  8. Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters. Cell 2014, 2014 Jul 17;158(2):412-21. doi: 10.1016/j.cell.2014.06.034.
  9. IMG/M: the integrated metagenome data management and comparative analysis system. Nucleic Acids Research 42 (Database-Issue): 568-573 (2014).
  10. IMG 4 version of the integrated microbial genomes comparative analysis system. Nucleic Acids Research 42 (Database-Issue): 560-567 (2014).
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