AdaptML

AdaptML infers ecologically differentiated populations within microbial communities by partitioning gene sequences using genetic and ecological data to reveal ecological specialization and evolutionary divergence.

Key Features:

• Quantitative Modeling: Employs a quantitative model that delineates the evolutionary history of ecological differentiation among microbial populations.
• Spatial and Temporal Resource Partitioning Analysis: Analyzes spatial and temporal resource partitioning to assess coexistence and competition in dynamic environments such as coastal bacterioplankton ecosystems.
• Phylogenetic Depth Resolution: Identifies ecological population boundaries that often align with deep phylogenetic levels, including named species.
• Detection of Adaptive Radiation: Detects signatures of recent or ongoing adaptive radiation, demonstrated by uncovering numerous ecologically distinct populations within Vibrio splendidus.
• Ecological Specialization Correlation: Assesses correlations between environmental specialization and potential speciation among sympatric microbes.

Scientific Applications:

• Microbial Ecology: Partitions gene sequences by ecological role to map functional diversity within microbial communities.
• Evolutionary Biology: Traces evolutionary histories and detects adaptive radiation to study speciation and genetic divergence.
• Environmental Microbiology: Explores microbial adaptation to environmental niches and associations with hosts or particles.

Methodology:

Integrates genetic data with ecological parameters to construct quantitative models that automatically partition gene sequences and analyze ecological factors such as seasonal changes and associations with hosts (free-living, particle, zooplankton) to reveal evolutionary trajectories.