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Correction to Biology 2025, 14(11), 1609.
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Correction

Correction: Wang et al. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609

by
Tongliang Wang
1,2,3,
Mengying Li
1,
Wanlu Ren
1,2,3,
Jun Meng
1,2,3,
Xinkui Yao
1,2,3,
Hongzhong Chu
4,
Runchen Yao
4,
Manjun Zhai
1,2 and
Yaqi Zeng
1,2,3,*
1
College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China
2
Xinjiang Key Laboratory of Horse Breeding and Exercise Physiology, Urumqi 830052, China
3
Horse Industry Research Institute, Xinjiang Agricultural University, Urumqi 830052, China
4
Xinjiang Yili Kazakh Autonomous Prefecture Animal Husbandry Station, Urumqi 835000, China
*
Author to whom correspondence should be addressed.
Biology 2026, 15(3), 209; https://doi.org/10.3390/biology15030209
Submission received: 19 January 2026 / Accepted: 19 January 2026 / Published: 23 January 2026
Browse Figures
Versions Notes
Error in Figure
In the original publication [1], there was a mistake in Figure 2B as published. When we submitted the higher-resolution images of the figures, we mistakenly inserted the image of Figure 2A in place of Figure 2B. As a result, the image of Figure 2A appears twice in the published version. The corrected Figure 2B appears below. The authors state that the scientific conclusions are unaffected.
This correction was approved by the Academic Editor. The original publication has also been updated. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Wang, T.; Li, M.; Ren, W.; Meng, J.; Yao, X.; Chu, H.; Yao, R.; Zhai, M.; Zeng, Y. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609. [Google Scholar] [CrossRef] [PubMed]
Biology 15 00209 g002aBiology 15 00209 g002bBiology 15 00209 g002c
Figure 2. (A) Principal Component Analysis (PCA) plot. PC1 denotes the first principle components, PC2 denotes the second principle components, and percentages indicate the proportion of variance in the dataset explained by PC1 and PC2. Each point in the graphic represents a sample; samples from the same group have the same color. “Group” denotes grouping; the same applies below. (B) A score plot developed using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). The predictive principal component is represented by the horizontal axis, whose direction indicates differences between groups; The orthogonal principal component is represented by the vertical axis, whose direction indicates intra-group differences; percentages show how well each component explains the dataset. Each point in the graphic represents a sample, with samples from the same group colored identically. (C) Volcano plot of differential lipids, where labeled lipids are core lipids with VIP values greater than two and significance to the research topic. (D) Heatmap of core differential lipids. (E) KEGG Pathway Enrichment Analysis of Differential lipids.
Figure 2. (A) Principal Component Analysis (PCA) plot. PC1 denotes the first principle components, PC2 denotes the second principle components, and percentages indicate the proportion of variance in the dataset explained by PC1 and PC2. Each point in the graphic represents a sample; samples from the same group have the same color. “Group” denotes grouping; the same applies below. (B) A score plot developed using Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). The predictive principal component is represented by the horizontal axis, whose direction indicates differences between groups; The orthogonal principal component is represented by the vertical axis, whose direction indicates intra-group differences; percentages show how well each component explains the dataset. Each point in the graphic represents a sample, with samples from the same group colored identically. (C) Volcano plot of differential lipids, where labeled lipids are core lipids with VIP values greater than two and significance to the research topic. (D) Heatmap of core differential lipids. (E) KEGG Pathway Enrichment Analysis of Differential lipids.
Biology 15 00209 g002aBiology 15 00209 g002bBiology 15 00209 g002c
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MDPI and ACS Style

Wang, T.; Li, M.; Ren, W.; Meng, J.; Yao, X.; Chu, H.; Yao, R.; Zhai, M.; Zeng, Y. Correction: Wang et al. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609. Biology 2026, 15, 209. https://doi.org/10.3390/biology15030209

AMA Style

Wang T, Li M, Ren W, Meng J, Yao X, Chu H, Yao R, Zhai M, Zeng Y. Correction: Wang et al. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609. Biology. 2026; 15(3):209. https://doi.org/10.3390/biology15030209

Chicago/Turabian Style

Wang, Tongliang, Mengying Li, Wanlu Ren, Jun Meng, Xinkui Yao, Hongzhong Chu, Runchen Yao, Manjun Zhai, and Yaqi Zeng. 2026. "Correction: Wang et al. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609" Biology 15, no. 3: 209. https://doi.org/10.3390/biology15030209

APA Style

Wang, T., Li, M., Ren, W., Meng, J., Yao, X., Chu, H., Yao, R., Zhai, M., & Zeng, Y. (2026). Correction: Wang et al. Multi-Omics Analysis Reveals Biaxial Regulatory Mechanisms of Cardiac Adaptation by Specialized Racing Training in Yili Horses. Biology 2025, 14, 1609. Biology, 15(3), 209. https://doi.org/10.3390/biology15030209

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