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    A vertical tree stump outdoors with about a dozen shiitake mushrooms sprouting from its surface.
    Tracing the Evolution of Shiitake Mushrooms
    Understanding Lentinula genomes and their evolution could provide strategies for converting plant waste into sugars for biofuel production. Additionally, these fungi play a role in the global carbon cycle.

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    Soil Virus Offers Insight into Maintaining Microorganisms
    Through a collaborative effort, researchers have identified a protein in soil viruses that may promote soil health.

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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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    Mapping Switchgrass Traits with Common Gardens
    The combination of field data and genetic information has allowed researchers to associate climate adaptations with switchgrass biology.

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    Artist rendering of genome standards being applied to deciphering the extensive diversity of viruses. (Illustration by Leah Pantea)
    Expanding Metagenomics to Capture Viral Diversity
    Along with highlighting the viruses in a given sample, metagenomics shed light on another key aspect of viruses in the environment — their sheer genetic diversity.

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    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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    Silver Age of GOLD Introduces New Features
    The Genomes OnLine Database makes curated microbiome metadata that follows community standards freely available and enables large-scale comparative genomics analysis initiatives.

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    A Better Way to Find RNA Virus Needles in the Proverbial Database Haystacks
    Researchers combed through more than 5,000 data sets of RNA sequences generated from diverse environmental samples around the world, resulting in a five-fold increase of RNA virus diversity.

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    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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    Final Round of 2022 CSP Functional Genomics Awardees
    Meet the final six researchers whose proposals were selected for the 2022 Community Science Program Functional Genomics call.

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    CSP New Investigators FY23 R1
    JGI Announces First Round of 2023 New Investigator Awardees
    Twice each year we look for novel research projects aligned with DOE missions and from PIs who have not led any previously-accepted proposals through the CSP New Investigator call.

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    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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    2022 JGI-UC Merced interns (Thor Swift/Berkeley Lab)
    Exploring Possibilities: 2022 JGI-UC Merced Interns
    The 2022 UC Merced intern cohort share how their summer internship experiences have influenced their careers in science.

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    Using Team Science to Build Communities Around Data
    As the data portals grow and evolve, the research communities further expand around them. But with two projects, communities are forming to generate high quality genomes to benefit researchers.

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    Cow Rumen and the Early Days of Metagenomics
    Tracing a cow rumen dataset from the lab to material for a hands-on undergraduate research course at CSU-San Marcos that has since expanded into three other universities.

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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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