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Contrasting Clade-Specific Relative Evolutionary Rates for Site-Level Adaptation Analyses

This study demonstrates that analyzing clade-specific Relative Evolutionary Rate (RER) shifts offers a powerful complementary approach to traditional dN/dS methods for detecting site-level adaptations, particularly by revealing biologically meaningful signals of past adaptive events followed by intensified purifying selection that standard metrics often miss.

Original authors: Facundo M. Giorello, Joaquina Farias

Published 2026-09-02

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CC BY 4.0

Original authors: Facundo M. Giorello, Joaquina Farias

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Evolution is often imagined as a slow, steady march of change, but the genetic story of life is far more dynamic. At the heart of this story is a simple question: how do living things change to survive in new environments? Scientists have long relied on a specific method to answer this, looking for genes that seem to be changing faster than expected. This method compares two types of genetic mutations: those that change the instructions for building a protein, and those that do not. When the changing ones outnumber the silent ones, it suggests that nature is actively favoring a new trait, a process known as positive selection. However, this traditional approach has a blind spot. It is excellent at spotting a sudden burst of change, but it often misses the quieter, more subtle shifts that happen after an animal has already adapted. Once a species finds a new way to survive, the rules of the game change; the specific parts of its proteins that are now essential become locked in place, while other parts might become more flexible. Detecting these shifts in the "rules" of evolution, rather than just the speed of change, has been a difficult challenge.

A team of researchers set out to solve this problem by looking at the genetic history of whales and their land-dwelling relatives. They focused on the dramatic transition from land to water, a shift that required massive changes in how these animals breathe, see, and move. Instead of just counting how many mutations occurred, the team developed a new way to measure the relative speed of evolution at every single building block of a protein. They asked a different question: for a specific spot in a protein, does it evolve at a different rate in whales compared to cows or deer? By comparing over 8,000 matching genes across 32 different species, including 17 whales and dolphins, they could see where the evolutionary "pace" had shifted specifically in the aquatic lineage.

The results revealed a powerful new way to see the past. The researchers found that their new method agreed with the traditional approach on many genes, confirming that both techniques were spotting real biological signals. But the new method also uncovered hundreds of genes that the traditional approach had completely missed. These hidden genes were not random noise; they formed a tightly connected network of proteins that work together, suggesting they were all part of the same grand adaptation to life in the ocean. Among the genes found only by this new method were those involved in blood clotting, lung function, and vision—systems that had to be completely rewired for underwater life. For instance, the study identified genes related to how whales manage oxygen and how their lungs handle the pressure of deep diving, which had not been flagged as important by previous methods.

One of the most significant findings was the discovery of genes that act as switches for how the body responds to low oxygen levels. These genes, which had been studied in animals living at high altitudes, appeared to be playing a crucial role in the evolution of whales. The researchers also found genes that help regulate the heart and the immune system in the lungs, all of which showed a distinct change in their evolutionary speed specifically in the whale lineage. This suggests that the new method is not just a backup plan, but a unique tool that can see the "footprint" of adaptation even when the classic signs of rapid change are absent.

The study does not claim to have found every single gene involved in the whale's journey to the sea, nor does it say that every gene it found is definitely the cause of a specific trait. The researchers acknowledge that their method can sometimes confuse a relaxed environment with an adaptive one, and it cannot always pinpoint exactly which species experienced the change first. However, the fact that the genes they found are biologically sensible and interconnected gives strong support to their hypothesis. By looking at how the rules of evolution change after a species adapts, rather than just looking for the speed of change itself, scientists can now see a much clearer picture of how life transforms to meet new challenges. This approach offers a fresh lens on the genetic history of life, revealing that the story of adaptation is written not just in the speed of change, but in the shifting landscape of what is allowed to change.

Technical Summary: Contrasting Clade-Specific Relative Evolutionary Rates for Site-Level Adaptation Analyses

Problem Statement
Detecting genetic adaptations is fundamental to evolutionary biology, yet traditional methods relying on the ratio of non-synonymous to synonymous substitution rates ( $dN/dS$ ) often fail to capture nuanced evolutionary processes. While positive selection is known to drive bursts of non-synonymous substitutions, it can also alter the intensity and spatial constraints of subsequent purifying selection following a single adaptive amino acid substitution. Current $dN/dS$ approaches are limited in their ability to detect these subtle shifts in the "space" of purifying selection, particularly when they do not result in a classic signature of pervasive positive selection ( $dN/dS > 1$ ). The authors propose that clade-specific shifts in Relative Evolutionary Rate (RER) at the site level may reveal a distinct footprint of purifying selection that reflects past adaptive events, offering a complementary perspective to traditional substitution rate ratios.

Methodology
The study utilized a dataset of over 8,000 single-copy orthologous genes across 32 artiodactyl species, comprising 17 cetaceans (CETA clade) and 15 terrestrial species (TERR clade), including bovids, caprids, cervids, and others. The workflow involved:

Data Curation and Alignment: Coding sequences (CDS) and protein sequences were retrieved from NCBI RefSeq. Orthology was inferred using OrthoFinder2. Alignments were generated using MACSE v2.03 for translation and MUSCLE v3.8.1551 for alignment. Stringent trimming was performed using TrimAl to remove gaps and low-similarity regions, followed by error filtering using BUSTED-E (HyPhy) to mask misalignments and prevent false positives.
Phylogenetic Reconstruction: Separate phylogenetic trees were constructed for the CETA and TERR clades based on established literature (McGowen et al., 2020; Chen et al., 2019).
RER Estimation: Site-level RER was estimated separately for each clade using LEISR (Local Evolutionary Rate Inference for Sites), a tool that scales per-site rates to the average protein rate. RER values were z-score transformed. Sites with non-overlapping confidence intervals between clades were identified as having significantly different evolutionary rates.
$dN/dS$ Analysis: To serve as a comparative baseline, the same alignments were scanned for pervasive diversifying selection using Fixed Effects Likelihood (FEL) in HyPhy. Sites with $p \le 0.05$ and $dN/dS > 1$ were considered under positive selection.
Comparative and Network Analysis: The study compared the overlap of significant genes and sites between the RER and FEL approaches. Protein-Protein Interaction (PPI) networks were constructed using STRING to evaluate the functional connectivity of gene sets identified exclusively by RER, exclusively by FEL, and those shared by both.

Key Results

Significant Overlap: The RER and FEL approaches identified a highly significant overlap in genes and sites. In the CETA clade, 95 genes were identified by both methods (hypergeometric $p < 1 \times 10^{-31}$ ), with both methods pinpointing the exact same site in 50% of these shared genes ( $p < 1 \times 10^{-88}$ ). Similar, though less pronounced, significant overlaps were found for the TERR clade.
Unique RER Signals: The RER approach identified 592 genes exclusively (not detected by FEL). PPI network analysis revealed that these "Unique RER" gene sets, particularly those where CETA sites evolved faster than TERR sites, exhibited the most significant protein-protein interaction enrichment ( $p = 5.47 \times 10^{-9}$ ), surpassing the significance of gene sets identified solely by traditional $dN/dS$ methods.
Biological Relevance: The unique RER genes included known candidates for cetacean adaptation (e.g., CPT2, FVII, RXFP1, ABCA3) and novel candidates with plausible roles in aquatic adaptation. Notable novel findings included:
- EPAS1 and NPAS4: Transcription factors involved in hypoxia response and neurogenesis, respectively, showing higher RER in cetaceans.
- TBXS1 and CNGB3: Genes related to blood clotting and vision, respectively.
- ALCAT1 and SFTPA: Genes linked to cardiac function and pulmonary surfactant/innate immunity.
- PLG: A gene in the same pathway as PLAU, previously highlighted in cetacean evolution for clot dissolution.

Significance and Claims
The paper claims that contrasting clade-specific RERs provides a valuable complement to $dN/dS$ -based analyses for identifying sites under selection. The authors argue that RER offers distinct advantages by conceptualizing purifying selection in a relative manner, capturing shifts in the "space" of equivalent amino acids that may follow an adaptive event without necessarily triggering a $dN/dS > 1$ signal.

The study demonstrates that genes identified exclusively through RER are biologically meaningful, showing high functional connectivity and involvement in known adaptive pathways (e.g., hypoxia, lung function, vision). The authors conclude that RER-based analyses possess intrinsic utility for uncovering adaptive processes that lack typical positive selection signals, rather than merely serving as a proxy for $dN/dS$ .

Limitations Acknowledged
The authors note several limitations: RER comparisons cannot detect adaptive events if evolutionary rates remain constant between clades despite amino acid changes; they cannot definitively identify which specific clade experienced the adaptive event; and RER differences can arise from relaxed selection (neutral processes) rather than positive selection. Furthermore, the high-throughput nature of the analysis required conservative filtering, which may bias rate estimations.

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