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Data-driven guidelines for phylogenomic analyses using SNP data.

Jacob S Suissa1, Gisel Y De La Cerda2, Leland C Graber3

  • 1Department of Ecology and Evolutionary Biology University of Tennessee at Knoxville Knoxville Tennessee USA.

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|December 4, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Filtering single-nucleotide polymorphisms (SNPs) for phylogenomic analysis should avoid strict thresholds. Using SNPs or locus data impacts branch lengths but not overall tree topology or divergence times.

Keywords:
Glycineancestral state reconstructionsdivergence time estimationgenotyping‐by‐sequencing (GBS)locusphylogenetic comparative methodssingle‐nucleotide polymorphism (SNP) filtering

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Area of Science:

  • Genomics
  • Phylogenetics
  • Evolutionary Biology

Background:

  • Best practices for filtering single-nucleotide polymorphisms (SNPs) in phylogenomic analyses are debated.
  • The choice between using SNPs or entire loci (including flanking regions) for phylogenetic inference remains unclear.

Purpose of the Study:

  • To assess the impact of SNP versus locus usage on phylogenomic analyses.
  • To evaluate the effects of SNP retention stringency on phylogenetic results.
  • To compare branch length, node support, and divergence time estimation under different filtering scenarios.

Main Methods:

  • Utilized genotyping-by-sequencing data from 22 *Glycine* species.
  • Compared 16 datasets with varying SNP retention stringency and data types (SNP vs. locus).
  • Analyzed effects on tree topology, branch length, node support, and divergence time estimation.

    • Main Results:

    • Tree topology remained largely congruent across different datasets.
    • Strict SNP filtering (90-100% retention) reduced node support and could alter inferred relationships.
    • Absolute branch lengths varied significantly between SNP and locus datasets (by two orders of magnitude).
    • Data type and branch length variation had minimal impact on divergence time estimation.
    • Phylograms influenced the estimation of ancestral states and morphological evolution rates.

    Conclusions:

    • SNP or locus datasets yield similar phylogenetic inferences unless absolute branch lengths are critical.
    • Excessive filtering thresholds for SNP retention are not recommended due to potential inconsistencies in topology and reduced support.
    • Researchers should carefully consider SNP filtering stringency to maintain robust phylogenetic signal.