Evidence map›Paper›PMID 40442598›Full record

ArticleBMC genomics2025

Characterizing age-related features for assessing biological age and characteristics in Xinjiang Brown cattle.

Jiahao Wang, Menghua Zhang, Qingyao Zhao, Siqian Chen, Yongjie Tang, Quanzhen Chen, Lei Xu, Dan Wang, Xiaoping Guo, Kai Xing and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC genomics, 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

14 authors.

Jiahao Wang *National Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Menghua Zhang *College of Animal Sciences, Xinjiang Agricultural University, Urumqi, 830052, China.
Qingyao ZhaoNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Siqian ChenNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Yongjie TangNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Quanzhen ChenNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Lei XuCollege of Animal Sciences, Xinjiang Agricultural University, Urumqi, 830052, China.
Dan WangCollege of Animal Sciences, Xinjiang Agricultural University, Urumqi, 830052, China.
Xiaoping GuoAnimal Husbandry Station of Yili Kazak Autonomous Prefecture, Yining, Xinjiang, 835000, China.
Kai XingNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Yachun WangNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
ChuduanWangNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Xixia HuangCollege of Animal Sciences, Xinjiang Agricultural University, Urumqi, 830052, China. au-huangxixia@163.com.
Ying YuNational Engineering Laboratory for Animal Breeding, State Key Laboratory of Animal Biotech Breeding, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China. yuying@cau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProductive lifespan is a critical economic trait for both dual-purpose and dairy cows, as it determines lifetime milk production. Xinjiang Brown cattle, a dual-purpose breed widely raised in China's Xinjiang region, have a population of nearly two million and play a vital role in the local economy. However, the molecular mechanisms influencing aging and productive lifespan in Xinjiang Brown cattle remain largely unknown. In this study, we collected white blood cell (leukocyte) transcriptome data from 66 Xinjiang Brown cattle, aged 31 to 160 months, to investigate the dynamic changes in their gene expression profiles across different ages and identify genes potentially influencing their aging process.

resultsA total of 1140 genes were identified as exhibiting a linear change in expression with age, while 697 genes showed non-linear changes, mainly enriched in immune and disease-related pathways. Linear genes were selected using elastic network regression to construct a transcriptomic clock and estimate the biological age of each sample. Individuals with older biological ages trend to highly express aging-related genes such as S100A8, while individuals with younger biological ages will highly express anti-aging genes such as BLVRB. We identified PGA5, LOC789748, ENSBTAG00000048555, and ENSBTAG00000050566 as crucial targets for anti-aging interventions, which exhibit reduced expression in biologically younger individuals and increased expression in biologically older ones. Performing sliding window analysis on non-linear genes, we elucidated changes in the expression of candidate genes at the age of 67 months, which are predominantly associated with endocrine pathways, such as GnRH and insulin secretion.

conclusionsThis study characterized the age-related gene expression changes in Xinjiang Brown cattle and developed a transcriptomic clock specifically for calculating their biological age. It provides a valuable tool for assessing the aging status of Xinjiang Brown cattle and identifies key genes that may influence their aging process.

Indexed as

AgingTranscriptomeAnimalsCattleChinaFemaleGene Expression ProfilingLeukocytesAgingBiological ageDual-purpose cattleTranscriptomic clock

Identifiers

PMID40442598
PMCPMC12121290

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LicenceCC BY-NC-ND
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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.