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Evolutionary Relationships through Genome Comparisons

Evolutionary Relationships through Genome Comparisons

Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

Multi-species Conserved Sequences

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Next-generation sequencing technologies have created large genomic databases of a variety of animals and plants. Ever since the human genome project was completed, scientists studied the genome of primates, mammals, and other phylogenetically distant living beings. Such large-scale studies have provided new insights into the evolutionary relationship between organisms.
Although the genome of each species varies greatly from each other, a few sequences are highly conserved. Such conserved...

Phylogeny

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Phylogeny is concerned with the evolutionary diversification of organisms or groups of organisms. A group of organisms with a name is called a taxon (singular). Taxa (plural) can span different levels of the evolutionary hierarchy. For instance, the group containing all birds is a taxon (comprising the class Aves), and the group of all species of daisies (the genus Bellis) is a taxon. Phylogenies can likewise include just one genus (i.e., depict species relationships) or span an entire kingdom.

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Updated: May 1, 2026

A Concoction Pipeline for Generating Molecular Operational Taxonomic Units (MOTUs) Among Riparian and Aquatic Beetles

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Phylogenetic Placement Using SCAMPP and Batch-SCAMPP.

Eleanor Wedell¹, Chengze Shen¹, Tandy Warnow²

¹Siebel School of Computing and Data Science, University of Illinois Urbana-Champaign, Urbana, IL, USA.

Methods in Molecular Biology (Clifton, N.J.)

|April 29, 2026

Summary

This summary is machine-generated.

SCAMPP and Batch-SCAMPP enhance phylogenetic placement accuracy for large trees. These methods improve scalability for tools like pplacer and EPA-ng, aiding metagenomics and tree construction.

Keywords:

Abundance profiling EPA-ng Large phylogenies Maximum likelihood Microbiome analysis Phylogenetic placement Pplacer Taxon identification

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Area of Science:

Computational Biology
Bioinformatics
Phylogenetics

Background:

Phylogenetic placement is crucial for understanding evolutionary relationships.
Maximum likelihood methods (e.g., pplacer, EPA-ng) offer high accuracy but struggle with large datasets.
Scalability limitations hinder the application of accurate phylogenetic placement methods to very large trees.

Purpose of the Study:

To introduce SCAMPP and Batch-SCAMPP, novel methods designed to enhance the scalability of phylogenetic placement.
To maintain high accuracy while enabling the analysis of very large phylogenetic trees.
To demonstrate the utility of these methods in metagenomics and tree-building applications.

Main Methods:

Development of SCAMPP and Batch-SCAMPP algorithms to optimize phylogenetic placement scalability.
Integration of these methods to work with existing maximum likelihood tools (pplacer, EPA-ng).
Application of SCAMPP and Batch-SCAMPP in metagenomic analyses and incremental tree growth scenarios.

Main Results:

SCAMPP and Batch-SCAMPP significantly improve the scalability of phylogenetic placement for large trees.
These methods maintain high accuracy comparable to existing tools.
Successful application demonstrated in metagenomics for taxon identification and abundance profiling.

Conclusions:

SCAMPP and Batch-SCAMPP effectively address the scalability limitations of current phylogenetic placement methods.
These tools enable accurate analysis of large-scale phylogenetic data, advancing fields like metagenomics.
The open-source availability of SCAMPP and Batch-SCAMPP facilitates broader adoption and research.