Evidence map›Paper›PMID 41348106›Full record

ArticleAnimal biotechnology2025

Genetic diversity assessment of Guangling Large-Tail sheep and introduced breeds in Shanxi Province using microsatellite markers and inference of heterosis potential.

Lina Xue, Jingyu Chen, Boting Li, Shenghua Zhou, Hongyu Guo, Li Zhang, Jun Li, Zhiwu Wang

Abstract read
In one paragraph

Article in Animal biotechnology, 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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Animals : an open access journal from MDPI · 2026
    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.

Lina XueCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Jingyu ChenCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Boting LiCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Shenghua ZhouCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Hongyu GuoCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Li ZhangCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Jun LiCollege of Animal Science, Shanxi Agricultural University, Taigu, China.
Zhiwu WangCollege of Animal Science, Shanxi Agricultural University, Taigu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was designed to assess the genetic diversity and population genetic structure of five sheep breeds in Shanxi Province, China, and to infer the heterosis potential based on their genetic relationships using 20 genome-wide microsatellite markers. Our analysis focused on the local Guangling Large Tail Sheep (GLLTS) breed and four introduced breeds: Hu Sheep (HS), Oula Tibetan Sheep (OLTS), Texel Sheep (TS), and Small Tail Han Sheep (STHLS). The results demonstrated that all microsatellite loci exhibited high levels of polymorphism, making them suitable for evaluating genetic diversity. The genetic parameters indicating that the five populations possess substantial genetic diversity. The genetic variation index (Fst) results among the five populations showed that moderate differentiation between populations. The genetic structure analysis results and the UPGMA clustering diagram were largely consistent. TS exhibited a distant genetic relationship with the other breeds, while HS and GLLTS shared the closest genetic relationship. Based on these genetic evidences, crossing GLLTS with TS or STHLS could potentially achieve a greater degree of heterosis. These research findings provide a molecular genetic foundation for analyzing the genetic diversity of sheep in Shanxi Province and offer guidance for hybrid breeding programs aimed at optimizing breed performance and resource conservation.

Indexed as

Genetic VariationHybrid VigorMicrosatellite RepeatsAnimalsBreedingChinaSheepgenetic diversityGuangling large-tailed sheepheterosis potentialmicrosatellite markerssheep

Identifiers

PMID41348106
PMCPMC12875336

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.