B-STILL: Evolutionary stasis constraints#

 About This Paper Method
Beyond Invariable Sites: Using Evolutionary Stasis to Map Multi-Layered Constraints on the Evolution of Viral and Mammalian Genomes
Authors: Sergei L. Kosakovsky Pond, Hannah Verdonk, Steven Weaver, Gallean Brown, Danielle Callan, Anton Nekrutenko, Darren P. Martin
Reference: Preprint, 2026. DOI: 10.1101/2026.04.09.717527

Method Summary#

B-STILL (Bayesian Significance Test of Invariant Low Likelihoods) is a hierarchical Bayesian framework designed to map extreme purifying selection at invariant (unchanging) sites in protein-coding genomes.

Standard phylogenetic tools rely on amino acid and nucleotide variation to estimate evolutionary rates. Consequently, whenever a site is completely invariant across an alignment, these tools face a resolution gap. They cannot distinguish between: 1. Stochastic Stasis: The site has not mutated simply due to chance or low divergence. 2. Functional Constraint: The site is biologically incapable of tolerating mutations.

B-STILL solves this by estimating a site-specific "stasis radius" and calibrating it against the gene's overall evolutionary rate and tree-level mutational opportunities. It identifies statistically anomalous invariant sites, labeling them as Evolutionary Stasis Anchors (ESAs).

What It Does#

  • Identifies Stasis Anchors: Maps sites where mutations are actively suppressed, revealing deep purifying selection.
  • Tackles Invariant Resolution Gap: Computes the probability that a site's invariance is driven by biological constraint rather than a lack of evolutionary time.
  • Scalable to Large Alignments: Operates efficiently on coding alignments containing thousands of sequences, making it suitable for modern genomic datasets.

How to Use It in HyPhy#

B-STILL is implemented in HyPhy and can be executed via HBL scripts:

  1. Prepare Input: You need a coding sequence alignment and a corresponding phylogenetic tree.
  2. Run the Analysis: Execute the B-STILL script in HyPhy: bash hyphy bstill --alignment data.fas --tree tree.nwk
  3. Analyze Outputs: The output JSON provides site-specific Bayes factors and probabilities. Sites with high significance support are flagged as Evolutionary Stasis Anchors (ESAs).

Key Findings & Significance#

  • Biological Fitness Predictor: Validation against clinical databases and pathogen experimental datasets confirms that ESAs are strong predictors of viral fitness and clinical disease potential.
  • Footprints Protein Domains: Automatically maps and footprints functional protein domains and currently uncharacterized structural motifs in mammalian and viral genomes.
  • Transforms Formerly Ignored Data: Salvages invariant sites—traditionally discarded or treated as background noise in phylogenetic trees—into useful markers of extreme purifying selection.