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Animals
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Advancing Cattle Breeding and Production Through Genomics, Phenotyping, Bioinformatics, and...
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Advancing Cattle Breeding and Production Through Genomics, Phenotyping, Bioinformatics, and Sustainable Practices

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Cattle".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 1675

Special Issue Editors

Dr. Vinicius Silva Junqueira

E-Mail Website
Guest Editor
Bayer Crop Science, Minas Gerais, Uberlândia 38057-049, Brazil
Interests: animal breeding; genomics; bioinformatics; statistics; big data
Dr. Jorge Hidalgo

E-Mail Website
Guest Editor
Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA
Interests: genetics; genomics; livestock; statistical genetics
Special Issues, Collections and Topics in MDPI journals
Dr. Gabriel Soares Campos

E-Mail Website
Guest Editor
Interbull Centre, Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences (SLU), P.O. Box 7023, 750 07 Uppsala, Sweden
Interests: cattle breeding; genomics; genetic evaluation; statistics
Dr. Delvan Alves da Silva

E-Mail Website
Guest Editor
Department of Animal Science, Federal University of Viçosa, Viçosa, MG, Brazil
Interests: cattle breeding; genomics; genetic evaluation; genotype by environment interaction

Special Issue Information

Dear Colleagues,

Recent advances in genomics, phenotyping technologies, and bioinformatics have opened new possibilities for improving cattle breeding and production systems. These approaches enable more accurate selection, accelerated genetic gain, and a deeper understanding of the complex traits related to growth, fertility, disease resistance, environmental resilience, and robustness. At the same time, sustainable practices in livestock management are becoming increasingly important to address global challenges such as climate change, resource efficiency, and animal welfare.

This Special Issue aims to provide a platform for the latest research and innovations that integrate genomic technologies, advanced phenotyping, and data-driven tools with sustainable cattle production systems. We welcome studies that demonstrate how these combined approaches can enhance productivity, genetic diversity, and long-term viability of beef and dairy production.

The Special Issue welcomes original research articles, reviews, and case studies covering, but not limited to, the following topics:

-Genomic selection, genome-wide association studies (GWAS), and gene editing in cattle;
-High-throughput phenotyping and precision livestock technologies;
-Applications of bioinformatics and big data in cattle breeding;
-Multi-omics approaches (e.g., genomics, phenomics, transcriptomics, metabolomics);
-Integration of genetics and nutrition for improved feed efficiency;
-Breeding strategies for climate resilience, robustness, and disease resistance;
-Sustainability and environmental impact of modern breeding programmes;
-Genetic diversity conservation in cattle populations;
-Ethical, economic, and policy considerations in genomic-based breeding.

Dr. Vinicius Silva Junqueira
Dr. Jorge Hidalgo
Dr. Gabriel Soares Campos
Dr. Delvan Alves da Silva
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • genomic selection
  • cattle breeding
  • high-throughput phenotyping
  • bioinformatics
  • feed efficiency
  • genetic improvement

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Published Papers (3 papers)

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Research

15 pages, 763 KB  
Article
Verification of Accuracy of Genomically Enhanced Predicted Transmitting Ability Techniques in Predicting Milk and Fat Production in Holstein Cattle in Taiwan
by Chun-Hsuan Chao and Jen-Wen Shiau
Animals 2025, 15(22), 3334; https://doi.org/10.3390/ani15223334 - 19 Nov 2025
Viewed by 324
Abstract
This study evaluated the predictive performance of genomically enhanced predicted transmitting abilities for milk (gPTAM) and fat yield (gPTAF) in 986 first-lactation Holstein cows from 25 herds in Taiwan. Ordinary least squares and linear mixed models revealed significant positive associations between genomic predictions [...] Read more.
This study evaluated the predictive performance of genomically enhanced predicted transmitting abilities for milk (gPTAM) and fat yield (gPTAF) in 986 first-lactation Holstein cows from 25 herds in Taiwan. Ordinary least squares and linear mixed models revealed significant positive associations between genomic predictions and observed yields (milk: β = 1.201, R2 = 0.469; fat: β = 1.444, R2 = 0.507). Incorporating herd and birth-year effects improved model fit and reduced residual variability. Five-fold cross-validation confirmed the robustness of the full mixed model, with predictive R2 increasing to 0.293 for milk and 0.363 for fat, distinct from the OLS R2 (0.469 and 0.507) representing phenotypic variation explained, indicating moderate predictive ability of genomic PTA values under subtropical production conditions. Model adequacy checks supported appropriate model specification, with only a mild outlier signal in the milk model. Regional analysis revealed a significant genotype-by-environment interaction for PTAF (p = 0.018) but not for PTAM, indicating reduced prediction accuracy in environmentally variable regions and highlighting trait-specific environmental sensitivity. Quartile stratification by gPTA and Net Merit Score demonstrated clear yield gradients, confirming both the predictive and economic value of genomic evaluations under subtropical dairy production systems. Full article
(This article belongs to the Special Issue Advancing Cattle Breeding and Production Through Genomics, Phenotyping, Bioinformatics, and Sustainable Practices)
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18 pages, 273 KB  
Article
Assessment of Longevity and Lifetime Productivity of Local Cattle Breeds in Relation to International Breeds
by Wioletta Sawicka-Zugaj, Witold Chabuz, Joanna Barłowska, Sebastian Mucha and Andrzej Bochniak
Animals 2025, 15(22), 3312; https://doi.org/10.3390/ani15223312 - 17 Nov 2025
Viewed by 450
Abstract
This study was based on data obtained from a total of 9518 cows belonging to seven cattle breeds: local breeds—Polish White-Backed (249), Polish Red (269), Polish Black-and-White (255), and Polish Red-and-White (290)—and international breeds—Polish Holstein-Friesian (5917), Jersey (940), and Simmental (1598). The breeds [...] Read more.
This study was based on data obtained from a total of 9518 cows belonging to seven cattle breeds: local breeds—Polish White-Backed (249), Polish Red (269), Polish Black-and-White (255), and Polish Red-and-White (290)—and international breeds—Polish Holstein-Friesian (5917), Jersey (940), and Simmental (1598). The breeds were characterised in terms of the following parameters: length of life, length of productive life, milking life, longevity index, percentage share of yield in the first 305-day lactation and first complete lactation in the lifetime yield, and functional longevity. Reasons for culling and the relationship between the length of life/productive life and milk performance parameters were determined as well. The analysis of the length of life and length of productive life in seven different cattle breeds kept in Poland unequivocally demonstrates that local breeds clearly stand out in this regard in comparison to international breeds. They may in the future constitute a valuable gene reservoir for improving longevity in other breeds. The length of life of Polish White-Backed and Polish Red cows was 2817 days and 3607 days, respectively, while that of Polish Holstein-Friesian and Jersey cows was only 2131 and 1956 days, respectively, and the most common cause of culling of cows in Poland (39.07%), irrespective of breed, was reproductive problems. The favourable results of parameters related to the longevity of the local breeds of Polish Red and White-Backed show that they can become a tool for improving the longevity of international breeds. Full article
(This article belongs to the Special Issue Advancing Cattle Breeding and Production Through Genomics, Phenotyping, Bioinformatics, and Sustainable Practices)
15 pages, 4511 KB  
Article
Development of a 5K Liquid-Phase Genome-Wide Breeding Chip for Xinglong Buffalo
by Yuqing Jiao, Junming Jiang, Shiyuan Li, Taoyu Chen, Xinjun Qiu, Ke Cui, Boling Li, Si Chen, Qiaoling Chen, Li Du, Churiga Man, Lianbin Li, Fengyang Wang and Hongyan Gao
Animals 2025, 15(18), 2702; https://doi.org/10.3390/ani15182702 - 15 Sep 2025
Viewed by 536
Abstract
The Xinglong buffalo is a local swamp buffalo breed adapted to tropical regions in China. To facilitate the protection and utilization of valuable genetic resources, we first developed the breed-specific single nucleotide polymorphism (SNP) liquid-phase chip based on genotyping-by-target-sequencing (GBTS) technology. Whole-genome resequencing [...] Read more.
The Xinglong buffalo is a local swamp buffalo breed adapted to tropical regions in China. To facilitate the protection and utilization of valuable genetic resources, we first developed the breed-specific single nucleotide polymorphism (SNP) liquid-phase chip based on genotyping-by-target-sequencing (GBTS) technology. Whole-genome resequencing data from 143 buffaloes, resulting in 34,757,694 SNPs, were used to identify 1208 breed-specific and 2889 background sites. This chip also incorporates 965 functional SNP sites derived from literature, including SNPs significantly associated with immunity, reproduction, growth, and production. A total of 5062 SNP sites were successfully identified for the development of a 5K liquid-phase genome-wide breeding chip for the Xinglong buffalo. The validation of the chip using 93 samples showed a high detection rate with good repeatability and consistency. In addition, the chip exhibits strong capabilities in clustering and kinship analysis. Results of kinship analysis underscored the importance of a breed-specific chip for the Xinglong buffalo. These results highlight the advantages of a low-density, cost-effective, and breed-specific SNP chip for accurate genotyping. This chip will support future endeavors in molecular breeding, conservation, and genetic evaluation of Xinglong buffalo, thereby facilitating the sustainable utilization of this valuable indigenous germplasm resource. Full article
(This article belongs to the Special Issue Advancing Cattle Breeding and Production Through Genomics, Phenotyping, Bioinformatics, and Sustainable Practices)
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