Evidence map›Paper›PMID 42079148›Full record

ArticlebioRxiv : the preprint server for biology2026

Entrenchment of germline amino-acid differences in antibody affinity maturation.

Noam Harel, Kevin Sung, Will Dumm, Mackenzie M Johnson, David Rich, Julia Fukuyama, Hugh K Haddox, Frederick A Matsen

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Noam HarelComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0003-3913-6098
Kevin SungComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0002-7289-845X
Will DummComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0002-8617-476X
Mackenzie M JohnsonComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0002-3915-2023
David RichComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0009-0005-2501-4032
Julia FukuyamaDepartment of Statistics, Indiana University, Bloomington, IN, USA.ORCID 0000-0002-7590-5563
Hugh K HaddoxComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0001-8324-8324
Frederick A MatsenComputational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA, USA.ORCID 0000-0003-0607-6025

Funding

Blending deep learning with probabilistic mechanistic models to predict and understand the evolution and function of adaptive immune receptorsR01AI146028 · NIAID · FRED HUTCHINSON CANCER RESEARCH CENTER · PI MATSEN, FREDERICK ALBERT · 2019 to 2024
$3.4M
High-Performance Compute Cluster for Comprehensive Cancer and Infectious Diseases ResearchS10OD028685 · OD · FRED HUTCHINSON CANCER RESEARCH CENTER · PI BRADLEY, PHILIP · 2020 to 2020
$2.0M
NIAID NIH HHS R01 AI146028NIH HHS S10 OD028685
6 · The paper itself

Abstract

Entrenchment - epistasis that locks in amino acid differences between homologous proteins, so each disfavors substitutions toward the other's state - has been demonstrated along individual protein lineages over deep evolutionary time. Antibodies offer a unique system for studying entrenchment: multiple homologous germline V gene paralogs provide diverse starting points, and the rapid somatic evolution of affinity maturation generates dense phylogenies from which selection on germline-encoded residues can be inferred. Using DASM, a deep-learning model that separates selection from mutation in antibody repertoire data, we test for entrenchment across immunoglobulin heavy chain variable (IGHV) genes. We detect entrenchment at two levels of germline divergence, driven by different sources of epistasis. Within V gene families (up to ~20% amino acid divergence), entrenched sites cluster at the borders of the complementarity-determining regions (CDRs, the antigen-binding loops) and show high germline diversity. These sites contact antigen, light chain, and the heavy chain CDR3 loop, all of which are encoded independently of the IGHV germline. This pattern is consistent with epistasis from genetically uncoupled partners. Between V gene families, at deeper levels of divergence (25-40%), entrenchment additionally includes positions in the framework scaffold distant from binding interfaces, suggesting a larger contribution from intra-heavy-chain structural constraints. Observed mutation frequencies in human repertoires corroborate these predictions where data are sufficient. Together, these results demonstrate that the rapid somatic evolution of antibodies can serve as a lens for revealing epistatic constraints acting on germline-encoded residues, including constraints imposed by genetically uncoupled partners assembled during B cell development.

Identifiers

PMID42079148
PMCPMC13131580

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.