Evidence map›Paper›PMID 40452433›Full record

ArticleGenome biology and evolution2025

Insights into Convergent Evolution From Studying Amino Acid Patterns in Independent Lineages of Birds.

Chul Lee, Seoae Cho, Kyu-Won Kim, Dongahn Yoo, Matthew Davenport, Jae Yong Han, Hong Jo Lee, Gregory Gedman, Jean-Nicolas Audet, Erina Hara and 5 more

Abstract read
In one paragraph

Article in Genome biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

15 authors.

Chul LeeInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.ORCID 0000-0002-9403-0774
Seoae ChoeGenome, Inc., Seoul, Republic of Korea.
Kyu-Won KimResearch Institute of Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea.ORCID 0000-0002-2733-0646
Dongahn YooInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.ORCID 0000-0003-0033-3721
Matthew DavenportLaboratory of Neurogenetics of Language, The Rockefeller University, New York City, NY 10065, USA.ORCID 0000-0002-5699-6295
Jae Yong HanDepartment of Agricultural Biotechnology and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea.ORCID 0000-0003-3413-3277
Hong Jo LeeDepartment of Agricultural Biotechnology and Research Institute for Agriculture and Life Sciences, Seoul National University, Seoul, Republic of Korea.ORCID 0009-0000-4462-0779
Gregory GedmanLaboratory of Neurogenetics of Language, The Rockefeller University, New York City, NY 10065, USA.ORCID 0000-0001-6819-2019
Jean-Nicolas AudetLaboratory of Neurogenetics of Language, The Rockefeller University, New York City, NY 10065, USA.ORCID 0000-0002-0511-183X
Erina HaraInstitute for Genomic Medicine, Columbia University College of Physicians and Surgeons, New York, NY 10032, USA.ORCID 0009-0007-2915-2568
Miriam RivasIntegrated Laboratory Systems, Inc., Research Triangle Park, NC 27706, USA.ORCID 0000-0002-5620-1632
Osceola WhitneyDepartment of Biology, Division of Science, The City College of New York, New York, NY 10031, USA.ORCID 0000-0002-5701-7722
Andreas R PfenningComputational Biology Department, The School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0002-7390-5041
Heebal KimInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.ORCID 0000-0003-3064-1303
Erich D JarvisLaboratory of Neurogenetics of Language, The Rockefeller University, New York City, NY 10065, USA.ORCID 0000-0001-8931-5049

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vocal learning, the ability to imitate sounds, is a complex convergent trait crucial for spoken language and observed in a few independent lineages of mammals and birds. While convergences in gene expression have been found in vocal learning brain regions, amino acid convergences remain unclear. Here, we investigated whether avian vocal learning clades have amino acid convergences linked to their specialized trait. We developed a tool, Convergent Variant Finder, and applied it to an alignment of 48 species representing nearly all bird orders to identify convergent single amino acid variants among vocal learners and over 8,000 other polyphyletic species combinations. We discovered that the number of convergent variants was associated with the product of branch lengths of the most recent common ancestors of each species combination. The number of convergent variants in vocal learning clades did not exceed that of control species combinations. However, a subset of genes with vocal learner-specific convergent amino acid variants was enriched in the "learning" process, under positive selection, and significantly overlapped with gene sets for FOXP2 targets, singing-induced regulation in vocal learning nuclei, and differentially expressed in vocal learning nuclei. Moreover, we confirmed that the majority of convergent patterns in vocal learners were in the genomes of 363 species densely sampled across the avian tree. We propose that amino acid and nucleotide convergence accumulates at a steady state, with the rate proportional to divergence time. Selection associated with convergent traits, such as vocal learning, then likely acts on a subset of these changes.

Indexed as

Amino AcidsBirdsEvolution, MolecularVocalization, AnimalAnimalsAvian ProteinsLearningPhylogenyAmino AcidsAvian ProteinsB3GNT2convergent evolutionconvergent single amino acid variant (ConSAV)convergent variant finder (ConVarFinder)dopamine receptor D1B (DRD5)positive selectionproduct of original branch (POB) lengthssong nucleivocal learning

Identifiers

PMID40452433
PMCPMC12703197

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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.