Evidence map›Paper›PMID 40610894›Full record

ArticleBMC ecology and evolution2025

Exome analysis reveals species divergence in TYR and identifies species genetic markers in five endemic Macaca species on Sulawesi Island.

Xiaochan Yan, Nami Arakawa, Kanthi Arum Widayati, Laurentia Henrieta Permita Sari Purba, Fahri Fahri, Bambang Suryobroto, Yohey Terai, Hiroo Imai

Abstract read
In one paragraph

Article in BMC ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Xiaochan YanMolecular Biology Section, Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Japan. yanxch3@outlook.com.
Nami ArakawaResearch Center for Integrative Evolutionary Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan.
Kanthi Arum WidayatiDepartment of Biology, IPB University, Bogor, Indonesia.
Laurentia Henrieta Permita Sari PurbaDepartment of Biology, IPB University, Bogor, Indonesia.
Fahri FahriDepartment of Biology, Tadulako University, Palu, Indonesia.
Bambang SuryobrotoDepartment of Biology, IPB University, Bogor, Indonesia.
Yohey TeraiResearch Center for Integrative Evolutionary Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama, Japan. terai_yohei@soken.ac.jp.
Hiroo ImaiMolecular Biology Section, Center for the Evolutionary Origins of Human Behavior, Kyoto University, Inuyama, Japan. imai.hiroo.5m@kyoto-u.ac.jp.

Funding

JSPS Bilateral Joint Research Project JPJSBP 120188103KAKENHI from Japan Society for the Promotion of Science (JSPS) 21KK0130, 22H02674, and 23K23937
6 · The paper itself

Abstract

backgroundOne of the greatest challenges for evolutionary biologists is explaining the vast diversity observed in nature. On Sulawesi Island, macaque species (genus Macaca) have rapidly diverged from their common ancestor, displaying remarkable variability in body morphology and coat color. Despite low overall genetic variation among these macaques, limited hybridization occurs between neighboring species, possibly due to genomic divergence or local adaptations that act as barriers to interbreeding. This study aims to investigate highly divergent regions that might contribute to the distinct genetic and phenotypic characteristics differentiating the five Sulawesi macaque species. Additionally, it explores how these genetic differences influence biological functions, and identifies species-specific genetic markers for species identification and conservation.

resultsUsing whole exome sequencing of 46 individuals, approximately 550 highly divergent genes were identified across four pairwise species comparisons. Gene Ontology (GO) analysis revealed that these genes were enriched in critical biological processes, including cell adhesion, pigmentation, signal transduction, and stress responses. Among these, pigmentation-associated genes, such as TYR and LRIT3, exhibited highly divergent single nucleotide polymorphisms (SNPs). Missense mutations in TYR (D132N) and LRIT3 (S394P, Y363D) were likely linked to the dark coat colors of Macaca nigra and Macaca nigrescens, highlighting their contribution to species-specific traits. Furthermore, hundreds of fixed SNPs were identified as potential species-specific markers for species discrimination, providing valuable resource for distinguishing Sulawesi macaque species.

conclusionsThis study provides critical insights into the genetic mechanisms underlying species divergence and coat color variation in Sulawesi macaques. Highly divergent genomic regions between neighboring species likely contribute to species divergence and reinforce reproductive isolation. Enriched GO terms and pathways suggest that genetic divergence impacts key biological processes, including pigmentation, signal transduction, cell adhesion, and stress responses. Specifically, divergence in pigmentation-related genes such as TYR may play a role in interspecies differences in coat color, facilitating local adaptation, mate selection, and species identification. Additionally, the identification of species-specific genetic markers holds significant potential for conservation efforts, such as monitoring populations at risk of hybridization or genetic introgression. These findings advance our understanding of the genetic diversity in this unique primate group.

Indexed as

MacacaAnimalsExome SequencingGenetic MarkersGenetic VariationIslandsPigmentationPolymorphism, Single NucleotideSpecies SpecificityGenetic MarkersCoat colorFixationInterspecificMelanismTyrosinase

Identifiers

PMID40610894
PMCPMC12225481

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.