Evidence map›Paper›PMID 42001201›Full record

ArticleVeterinary research2026

Eco-evolutionary dynamics of a shifting porcine parvoviruses (PPV1-PPV8) ecosystem reveal dichotomous selection pressures.

Changchun Zhang, Zhiying Xu, Guangyu Liu, Huixin Li, Yunlan Ling, Lele Zhao, Xiaolong Xu, Yimin He, Ning Ding, Guihong Zhang and 1 more

Abstract read
In one paragraph

Article in Veterinary research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Changchun Zhang *Guangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Zhiying Xu *State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Guangyu LiuGuangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Huixin LiGuangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Yunlan LingGuangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Lele ZhaoNuffield Department of Medicine, Pandemic Sciences Institute, University of Oxford, Oxford, UK.
Xiaolong XuGuangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Yimin HeHipra Biotech Consulting (Beijing) Co., Ltd., Beijing, China.
Ning DingGuangzhou Customs Technology Center, Guangzhou, 510623, China. 79958704@qq.com.
Guihong ZhangGuangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China. guihongzh@scau.edu.cn.
Yankuo SunGuangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China. yankuosun@scau.edu.cn.

Funding

China Agriculture Research System of MOF and MARA, and the Specific University Discipline Construction Project 2023B10564003National Key Research and Development Program of China 2023YFD1301902the Guangzhou Science and Technology Plan Project 2023B04J0137
6 · The paper itself

Abstract

Porcine parvoviruses (PPVs) constitute a complex viral ecosystem. However, the genetic structure and evolutionary dynamics of currently circulating PPV populations remain poorly characterized. A large-scale genomic survey in China (1,055 genomes; 863 samples; 2021-2024) reveal a profound ecosystem shift, with PPVs detected in 212/863 samples (24.57%) Novel species (PPV7, 16.45%; PPV6, 9.62%; and PPV2, 8.82%) now dominate the niche previously occupied by classical PPV1 (3.13%). This new landscape is defined by pervasive multi-species co-infection (129/212, 60.85%), including 61 cases with ≥ 3 species and 7 pigs co-infected with ≥ 5 species, characterized by non-random associations, where even low-prevalence species such as PPV1 and PPV5 exhibit a high propensity for co-infection (permutation test: PPV1 p < 0.001; PPV5 p = 0.002). This high-transmission environment provides ample opportunities for frequent intra-species recombination, which powerfully accelerates variation within the primary antigenic region (ORF2). This study uncovered dichotomous evolutionary dynamics driven by contrasting immune pressure. The dominant naturally circulating species were constrained by strong purifying selection. In stark contrast, vaccine-targeted PPV1 followed a distinct path driven by strong positive selection of key surface epitopes (e.g., VP2 site 435), suggesting an adaptation to evade vaccine-induced immunity. Collectively, our work deconstructs how natural selection and vaccine filtering impose distinct selective regimes on the viral population, establishing a new framework for evolutionarily aware surveillance and rational design of next-generation vaccines.

Indexed as

Biological EvolutionEcosystemParvoviridae InfectionsParvovirus, PorcineSelection, GeneticSwine DiseasesAnimalsChinaCoinfectionEvolution, MolecularGenome, ViralSwineco-infectioneco-evolutionary dynamicsPorcine parvovirusesvaccine-induced selectionviral ecosystems

Identifiers

PMID42001201
PMCPMC13214466

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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.