Evidence map›Paper›PMID 40380299›Full record

ArticleBMC veterinary research2025

Selection signatures and inbreeding: exploring genetic diversity in five native horse breeds.

Vittoria Asti, Andrea Summer, Michela Ablondi, Cristina Sartori, Andrea Giontella, Valeria Pilastro, Samanta Mecocci, Katia Cappelli, Enrico Mancin, Angelica Oian and 3 more

Abstract read
In one paragraph

Article in BMC veterinary research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

13 authors.

Vittoria AstiDepartment of Veterinary Science, University of Parma, Parma, Italy.
Andrea SummerDepartment of Veterinary Science, University of Parma, Parma, Italy.
Michela AblondiDepartment of Veterinary Science, University of Parma, Parma, Italy. michela.ablondi@unipr.it.
Cristina SartoriDepartment of Agronomy, Natural Resources, Animals, and Environment, University of Padua, Food, Padua, Italy.
Andrea GiontellaDepartment of Veterinary Medicine, University of Perugia, Perugia, Italy.
Valeria PilastroDepartment of Veterinary Science, University of Parma, Parma, Italy.
Samanta MecocciDepartment of Veterinary Medicine, University of Perugia, Perugia, Italy.
Katia CappelliDepartment of Veterinary Medicine, University of Perugia, Perugia, Italy.
Enrico MancinDepartment of Agronomy, Natural Resources, Animals, and Environment, University of Padua, Food, Padua, Italy.
Angelica OianDepartment of Agronomy, Natural Resources, Animals, and Environment, University of Padua, Food, Padua, Italy.
Roberto Mantovani *Department of Agronomy, Natural Resources, Animals, and Environment, University of Padua, Food, Padua, Italy.
Stefano Capomaccio *Department of Veterinary Medicine, University of Perugia, Perugia, Italy.
Alberto Sabbioni *Department of Veterinary Science, University of Parma, Parma, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Horses have undergone extensive natural and artificial selection, shaping the diversity of breeds observed today. Native Italian breeds present unique traits influenced by natural selection, such as adaptation to harsh climates, or hoof strength, but face challenges due to population declines and the reduction of their original breeding purpose. This study focuses on five local Italian breeds: Bardigiano, Haflinger, Maremmano, Murgese, and Italian Heavy Draught Horse, to understand how selection has shaped their populations. A total of 1620 individuals were genotyped with a medium-density SNP chip and remapped to EquCab3. After quality control, where data were filtered based on missing genotypes per SNP (> 0.10) and missing SNPs per sample (> 0.10), 1498 horses and 54,825 SNPs remained for analysis. Population structure and runs of homozygosity (ROH) were identified, and genomic inbreeding coefficients were calculated based on ROH coverage of autosomal SNPs. ROH islands shared by ≥ 70% of horses were identified as selection signatures, and candidate genes within these regions were annotated. The inbreeding coefficient (FROH) ranged from 0.15 to 0.23, with Bardigiano and Haflinger showing the highest values probably due to selective breeding, while Maremmano, Murgese, and Italian Heavy Draught Horse displayed lower FROH, reflecting a broader diversity. ROH islands were identified on 12 chromosomes, with 23 islands distributed among breeds. Cold-blooded breeds (Bardigiano, Haflinger, and Italian Heavy Draught Horse) showed the majority, particularly on Equine Chromosome 3 (ECA3). These islands overlapped with 83 quantitative trait loci (QTLs) and 76 genes associated with morphology and health. Health-related traits such as osteochondrosis and hoof health were linked to ROH patterns, particularly in Bardigiano and Haflinger, highlighting selection for disease resistance. Signature of selections were found in the proximity of MC1R and ASIP genes likely due to their role for coat color; especially in the Haflinger and Italian Heavy Draught Horse the genotype frequency of the BIEC2_816499 SNP which is in the vicinity of the causative mutation for chestnut coat color is due to linkage disequilibrium between the two. In conclusion, this study offered valuable insights that breeders could utilize to make sound decisions. This issue would ensure the maintenance of breed genetic diversity, and the preservation and improvement of the breed's distinct traits and health standards.

Indexed as

Genetic VariationInbreedingSelection, GeneticAnimalsBreedingFemaleGenotypeHorsesItalyMalePolymorphism, Single NucleotideConservationGenotypeHealthHorse

Identifiers

PMID40380299
PMCPMC12082900

What OpenQuestion holds

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Registered trials

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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.