Evidence map›Paper›PMID 40941311›Full record

ArticleAnimals : an open access journal from MDPI2025

Population Genetic Structure, Historical Effective Population Size, and Dairy Trait Selection Signatures in Chinese Red Steppe and Holstein Cattle.

Peng Niu, Xiaopeng Li, Xueyan Wang, Huimin Qu, Hong Chen, Fei Huang, Kai Hu, Di Fang, Qinghua Gao

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Peng NiuCollege of Life Science and Technology, Tarim University, Alar 843300, China.ORCID 0000-0002-1710-4805
Xiaopeng LiCollege of Animal Science and Technology, Tarim University, Alar 843300, China.ORCID 0000-0003-0796-0795
Xueyan WangCollege of Animal Science and Technology, Tarim University, Alar 843300, China.
Huimin QuCollege of Animal Science and Technology, Tarim University, Alar 843300, China.ORCID 0009-0009-9340-6002
Hong ChenCollege of Life Science and Technology, Tarim University, Alar 843300, China.ORCID 0000-0002-1623-507X
Fei HuangCollege of Life Science and Technology, Tarim University, Alar 843300, China.ORCID 0000-0002-2611-0617
Kai HuCollege of Animal Science and Technology, Tarim University, Alar 843300, China.
Di FangCollege of Animal Science and Technology, Tarim University, Alar 843300, China.
Qinghua GaoCollege of Life Science and Technology, Tarim University, Alar 843300, China.

Funding

Establishment and Demonstration of Efficient Reproductive System in Cattle 2023A02011-1-1the Graduate Innovation Program of Tarim University, China TDBSCX202418 and TDGRI2024033
6 · The paper itself

Abstract

backgroundChinese Red Steppe cattle (CRS) combine indigenous environmental resilience with moderate dairy performance, whereas Holstein cattle (HOL), despite their high milk yield, suffer reduced genetic diversity and compromised adaptation. A comparative analysis of their population genetic architecture and selection signatures can reveal valuable targets for CRS dairy improvement.

methodsWe genotyped 61 CRS and 392 HOL individuals using the Illumina GGP Bovine 100K SNP array and performed stringent quality control. Population structure was assessed via principal component analysis, neighbor-joining trees, and sparse nonnegative matrix factorization. Historical effective population size (Ne) and divergence time were inferred with SMC++. Genome-wide selection scans combined Fixation Index (FST) and Cross-Population Composite Likelihood Ratio test (XP-CLR); overlapping high-confidence regions were annotated and subjected to GO and KEGG enrichment analyses.

resultsCRS and HOL were clearly separated along PC1 (explaining 57.48% of variance), with CRS exhibiting high internal homogeneity and weak substructure, versus greater diversity and complex substructure in HOL. SMC++ indicated a split approximately 3500 years ago (700 generations) and a pronounced recent decline in Ne for both breeds. Joint selection mapping identified 767 candidate genes; notably, the

conclusionThis study delineates the genetic divergence and demographic history of CRS and HOL, and pinpoints core genes and pathways-particularly those governing butanoate metabolism and protein quality control-underlying dairy traits. These findings furnish molecular markers and theoretical guidance for precision breeding and sustainable utilization of Chinese Red Steppe cattle.

Indexed as

ACSM genesbutanoate metabolismChinese red steppe cattleeffective population sizeFSTHolstein cattlepopulation structureSMC++XP-CLR

Identifiers

PMID40941311
PMCPMC12427281

What Socratic 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 Socratic graph.