This document outlines a roadmap for using metagenomic analysis to study the impact of long-term elevated carbon dioxide levels on soil microbial communities at several Department of Energy Free-Air Carbon Dioxide Enrichment (FACE) and Open Top Chamber (OTC) field sites. The goal is to assess how these belowground communities and their processes have responded over 10 years to elevated CO2 levels, and to compare responses across different ecosystems. A multi-tiered sequencing strategy is proposed to provide different levels of resolution and link findings back to field-scale responses and functions. Initial pilot studies are underway.
Objectives
Characterize the soil microbial community across different management practices and measure the corresponding greenhouse gas fluxes.
Determine the adaptation and acclimation of the soil microbial community climate change.
Improve a soil greenhouse gas emission model to predict greenhouse gas emissions under global change scenarios.
Microbiology has experienced a transformation during the last 25 years that has altered microbiologists' view of microorganisms and how to study them. The realization that most microorganisms cannot be grown readily in pure culture forced microbiologists to question their belief that the microbial world had been conquered. We were forced to replace this belief with an acknowledgment of the extent of our ignorance about the range of metabolic and organismal diversity.
GSB uses systems biology approaches like network analysis, modeling, and omics technologies to decipher the intricate web of relationships between organisms, genes, and environmental factors within ecosystems. This holistic approach helps reveal hidden patterns and dynamics that traditional reductionist methods might miss.
Objectives
Characterize the soil microbial community across different management practices and measure the corresponding greenhouse gas fluxes.
Determine the adaptation and acclimation of the soil microbial community climate change.
Improve a soil greenhouse gas emission model to predict greenhouse gas emissions under global change scenarios.
Microbiology has experienced a transformation during the last 25 years that has altered microbiologists' view of microorganisms and how to study them. The realization that most microorganisms cannot be grown readily in pure culture forced microbiologists to question their belief that the microbial world had been conquered. We were forced to replace this belief with an acknowledgment of the extent of our ignorance about the range of metabolic and organismal diversity.
GSB uses systems biology approaches like network analysis, modeling, and omics technologies to decipher the intricate web of relationships between organisms, genes, and environmental factors within ecosystems. This holistic approach helps reveal hidden patterns and dynamics that traditional reductionist methods might miss.
High-throughput sequencing data of microorganisms opens new perspectives for ...OECD Environment
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There is no replacement of the conventional breeding, but its limitations in terms of speed and accuracy can be overcome by molecular breeding programmes.
The conventional phenotyping and breeding approaches are sound, the advantages and opportunities thrown open by automated phenotyping should be availed for faster gains.
Since modern genotyping protocols are well developed and high throughput in rice, phenotyping models need more consideration because capturing “right QTL” largely depends upon right phenotyping.
In molecular breeding for salinity tolerance, initial success has been made by the discovery of many QTLs and several rice salinity GWAS reports, but still there is a considerable gap between knowledge discovery and actual use of molecular breeding in realization of field oriented salt tolerant rice varieties.
Stage-specific and stress-specific QTLs may be identified for need based deployment for which, the screening methodology should be simple and high throughput, reproducible and representative of near-field conditions.
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DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
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The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
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High-throughput sequencing data of microorganisms opens new perspectives for ...OECD Environment
24 June 2019: This OECD seminar presented and discussed the potential use of genome sequence, bioinformatic tools and databases in a regulatory decision process for microbial pesticides.
Breeding for salt tolerance in rice: Phenomics and genomicsPratik Satasiya
Harmonizing the high throughput techniques for phenomics and genomics is both a challenge and opportunity.
There is no replacement of the conventional breeding, but its limitations in terms of speed and accuracy can be overcome by molecular breeding programmes.
The conventional phenotyping and breeding approaches are sound, the advantages and opportunities thrown open by automated phenotyping should be availed for faster gains.
Since modern genotyping protocols are well developed and high throughput in rice, phenotyping models need more consideration because capturing “right QTL” largely depends upon right phenotyping.
In molecular breeding for salinity tolerance, initial success has been made by the discovery of many QTLs and several rice salinity GWAS reports, but still there is a considerable gap between knowledge discovery and actual use of molecular breeding in realization of field oriented salt tolerant rice varieties.
Stage-specific and stress-specific QTLs may be identified for need based deployment for which, the screening methodology should be simple and high throughput, reproducible and representative of near-field conditions.
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun SequencesSurya Saha
Presented at Cornell Symbiosis symposium. Workflow for processing amplicon based 16S/ITS sequences as well as whole genome shotgun sequences are described. Slides include short description and links for each tool.
DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
Carbon sequestration in agricultural soils: The “4 per mil” programExternalEvents
Carbon sequestration in agricultural soils: The “4 per mil” program presented by Hervé Saint Macary, Centre de coopération internationale en recherche agronomique pour le développement (CIRAD), Montpellier, France
TILLING AND ECO TILLING IN CROP IMPROVEMENT.pptxrushitahakik1
TILLING AND ECO TILLING in crop Improvement
A Reverse genetics Tool that enhences the potential to introduce specific mutation in oplants in order to improve crop diversity. i.e. Biotechnology beyound Genetically Modified crops.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
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Notes
Bibliography
All the contents are fully attributable to the author, Doctor Victor Salas. Should you wish to get this text republished, get in touch with the author or the editorial committee of the Studia Poinsotiana. Insofar as possible, we will be happy to broker your contact.
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Soil Metagenomics/Community Metagenomics.ppt
1. Roadmap for Soil Community Metagenomics
of DOE’s FACE & OTC Sites
Scientific Opportunity
Comprehensive, field-scale understanding of the responses of soil
microbial communities and their processes to long-term (10 yr) elevated
CO2, and comparison of responses across terrestrial ecosystems.
2. Goal
Develop a science & implementation plan based on metagenomic
technology, to assess responses of the belowground communities to
CO2 in DOE terrestrial ecosystem FACE and OTC sites.
Natural desert FACE
@ NTS; shrubs, grasses, crust
Natural scrub oak OTC
@ Cape Canaveral
Planted sweetgum
FACE @ ORNL
Planted aspen/maple/poplar
FACE @ Rhinelander
Planted pine FACE
@ Duke Univ.
Natural estuary OTC
@ Chesapeake Bay;
marsh grasses
DOE’s FACE & OTC sites
3. Core Competencies
Facilities:
FACE sites
JGI sequencing resources
other DOE facilities
People & Experience:
FACE site scientists
JGI personnel
National lab & University scientists
DOE program management
Objective
Establish a roadmap for implementing metagenomic
analysis of soil communities across several FACE sites
August 2007 Workshop
4. August Workshop Accomplishments
• Identified major ecological questions that should be addressed across the
FACE & OTC sites.
• Determined optimal sequencing technologies to answer those questions.
• Determined the best strategies for implementing sequencing technology in
these field-scale experiments.
• Discussed how best to coordinate sample, sequencing, & data management
Ecological Research Questions
• Within each site, has 10 yr elevated CO2 affected the soil microbial
community (abundance, composition) and ecosystem processes conducted
by this community?
• Have the soil communities in different ecosystems responded similarly or in
different patterns to elevated CO2?
5. Why Soil Metagenomics ?
Benefits & Potential Impacts
• Greatest source of biodiversity on Earth.
• Soil communities are central to multiple DOE mission
areas & potential for multiple impacts is high.
• Abundant biomass - large amounts of DNA for
multiple genomic studies.
Technical Challenges
• Diversity is high.
• Biofilms and physical attachment affect DNA.
extraction efficiency therefore standard protocols are
critical.
• Non-uniformity of substrates & patchiness so field
sample replication is essential.
• Fungal biomass is present & important, but fungal
genomes are complex.
6. Metagenomics ~ Community Genomics
any gene-based comparison
that spans across the collective microbial genome in an environment
TARGETED METAGENOMICS - focus on specific genes
Pros
• immediate link to function
• high depth of coverage in complex
community can provide strong
abundance/composition information
Cons
• single/few genes studied
• clone/sequence approaches are
thorough but time consuming
• only see what you know to look for
New Potential w/ 454 pyrosequencing
• larger panels of genes, multiple pathways
• resolution of sequencing without cloning
• larger number of sequences for each gene
• single pass sequencing w/ lower quality
7. SHOT-GUN METAGENOMICS
- clone & sequencing random fragments
Characteristics
• broad brush, ‘unbiased’ survey
• community complexity dictates
level of resolution & ability to link to
function
• functional interpretation is limited
due to our inability to ID genes in
the sequences obtained
• eukaryotic genomes have lower
probability of gene detection by
random sequencing
Bacterial cell
Eukaryotic cell
2-10 mb genome 30-100+ mb genome
Current Applications
• search for new enzymes
• describe microbial communities
• describe community dynamics
• compare community composition
Metagenomics ~ Community Genomics
8. Challenges & Novelty of Application of
Metagenomics to FACE/OTC Sites
• Comparative metagenomics, not just descriptive
• Strong need to tie to ecosystem function
• Similar parent material within a site
• Experimental framework w/ replication
• Link soil microbial results to field-scale ecology
• Will enhance & stretch our current sequencing technology
9. Hierarchical Research & Sequencing Strategy
Tiered datasets cross-inform to improve
our ability to interpret ecological relevance
100’s
10’s
Tier 1: Ability to relate metagenome data back
to field-scale soil response at FACE sites
Tier 3: Targeted metagenomics using 454 pyrosequencing
Tier 6: Shot-gun metagenomics
Tier 2: Phylogenetic species surveys
Tier 4: Transcriptome analysis of soil fungi
Tier 5: Seasonal, year-to-year patterns & ozone effects
10. Hierarchical Research & Sequencing Strategy
Tier 1 Measurements: Ability to relate metagenome data back to field-scale
soil response at FACE sites
In response to elevated CO2:
• has the microbial biomass changed?
• have functional properties or process measures changed?
• what is the variability across field replicates?
Tier 2 Sequencing: phylogenetic species surveys
In response to elevated CO2:
• has the relative abundance or composition of bacteria/fungi/archaea changed?
• has the relative abundance of the major phyla/species within a domain changed?
Tier 3 Sequencing: Targeted metagenomics using 454 pyrosequencing
In response to elevated CO2:
• has the functional diversity or composition been altered?
• how have key microbial species/processes been changed?
11. Hierarchical Research & Sequencing Strategy
Tier 4 Sequencing: Transcriptome analysis of soil fungi
In response to elevated CO2:
• has activity of abundant soil fungi changed?
• especially with regard to carbon utilization
Tier 5 Sequencing: Seasonal, year-to-year patterns & ozone effects
(Rhinelander site)
In response to elevated CO2 and/or ozone:
• how do changes relate to seasonal responses and year-to-year variability?
• how did soil communities respond to elevated ozone?
• were there any combined effects of elevated CO2 and ozone?
Tier 6 Sequencing: Shot-gun metagenomics
In response to elevated CO2:
• has the overall community been altered?
• what new properties are present?
• how do communities compare across sites?
12. Current Status
• Roadmap document circulated
to workshop participants and
DOE management.
• Two of the six FACE/OTC sites
have been deconstructed. Soil
samples are archived with the
primary site scientist and at
LANL.
• Pilot studies are in progress for
Tier 2 (rRNA surveys), Tier 3
(454 targeted metagenomics),
and Tier 4 (fungal transcriptome)
sequencing. Cheryl Kuske, kuske@lanl.gov