Application of Reproductive and Genomic Biotechnologies for Livestock Breeding and Selection: 2nd Edition

Topic Information

Dear Colleagues,

The worldwide demand for animal-derived products will increase dramatically in the next 30 years due to global population growth. Therefore, a comprehensive understanding of animal breeding through reproduction performance and genomic selection will be of the utmost importance to satisfy the growing food demand. In view of this, combining assisted reproductive techniques (ARTs) and genetic/genomic molecular tools (GMTs) for animal selection will play a key role in improving and maximizing animal production systems' efficiency. This Topic aims to present original research and/or reviews related to ARTs and GMTs. We welcome all studies on factors affecting livestock performance with a particular focus on reproduction management, health control, longevity improvement, and welfare practices based on ART- and GMT-derived results. Furthermore, we encourage studies that contribute significantly to further advancing these fields and those based on ARTs, such as in vitro fertilization (IVF), intracytoplasmic sperm injection (ICSI), in vitro/in vivo embryo production (IVP), embryo transfer (ET), controlled ovarian hyperstimulation (superovulation), gamete sex determination, artificial insemination (AI), gamete cryopreservation, nuclear transfer/cloning, stem cell technologies (SCTs), etc. Moreover, we invite contributions focused on complementary techniques for ARTs, including DNA isolation and analysis (DIA), polymerase chain reaction (PCR/rtPCR), DNA sequencing, recombinant plasmids, gene cloning, transgenesis, Southern blotting, single-nucleotide polymorphisms (SNPs), genome-wide association studies (GWASs), etc., are welcome as well.

Potential subtopics of interest include, but are not limited to, the following:

• The reproductive basis of important fertility traits;
• The application of ARTs to genetic resources for increasing reproductive/productive performance traits;
• Reproduction–nutrition interactions and efficient reproductive and production traits;
• Genes implicated in reproductive and production traits;
• Sequencing research surrounding breeding and genetics;
• Reproduction–health control interactions and efficient production traits;
• Biodiversity protection programs, germplasm banking, and ex situ preservation;
• Reproduction–welfare practices and efficient production traits;
• Reproduction–environment (climate) interactions and their impact on reproductive and production traits;
• Reproduction–longevity interactions for increasing fertility and productivity traits. We look forward to receiving your contributions.

Dr. Manuel García-Herreros
Prof. Dr. Pedro Manuel Aponte
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Animals animals	2.7	5.2	2011	17.7 Days	CHF 2400	Submit
Dairy dairy	3.1	4.9	2020	23.4 Days	CHF 1200	Submit
Genes genes	2.8	5.5	2010	14.6 Days	CHF 2600	Submit
Agriculture agriculture	3.6	6.3	2011	18 Days	CHF 2600	Submit
Poultry poultry	2.1	2.8	2022	34 Days	CHF 1200	Submit
Ruminants ruminants	1.3	2.0	2021	18.4 Days	CHF 1200	Submit
Veterinary Sciences vetsci	2.3	3.5	2014	21.1 Days	CHF 2100	Submit

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Open AccessArticle

Single-Cell Transcriptomic Profiling of Longissimus Dorsi and Biceps Femoris Muscles in Kazakh Horses Reveals Cellular Heterogeneity and Myogenic Regulation

by Jianwen Wang, Zexu Li, Luling Li, Ran Wang, Shikun Ma, Yi Su, Dehaxi Shan and Qiuping Huang

Animals 2025, 15(19), 2778; https://doi.org/10.3390/ani15192778 - 23 Sep 2025

Viewed by 312

Abstract

Kazakh horses are renowned for their endurance and adaptability, with distinct muscle groups such as the longissimus dorsi (LD) and biceps femoris (BF) muscles serving specialized functions. However, the molecular mechanisms underlying the functional specialization of these muscles in Kazakh horses remain poorly [...] Read more.

Kazakh horses are renowned for their endurance and adaptability, with distinct muscle groups such as the longissimus dorsi (LD) and biceps femoris (BF) muscles serving specialized functions. However, the molecular mechanisms underlying the functional specialization of these muscles in Kazakh horses remain poorly understood. This study aims to address this gap by utilizing single-cell RNA sequencing (scRNA-seq) to investigate the transcriptomic differences between these muscle groups, with a focus on understanding their molecular adaptations. Our analysis revealed that the BF muscle, specialized for explosive movements, exhibited upregulation of genes associated with anaerobic metabolism, muscle contraction, and oxidative stress response, reflecting its reliance on glycolysis for sustained energy production. In contrast, the LD muscle, primarily responsible for postural support and endurance, showed a metabolic shift toward lipid utilization and energy production. Differential gene expression analysis also revealed distinct enrichment in biological pathways, with LD cells being enriched in pathways related to muscle contraction and calcium signaling, while BF cells were enriched in energy metabolism pathways. These findings provide valuable insights into the molecular adaptations of Kazakh horses’ muscle tissues, highlighting the functional specialization of LD and BF muscles and offering a foundation for future research on improving muscle performance and breeding programs in equines. Full article

(This article belongs to the Topic Application of Reproductive and Genomic Biotechnologies for Livestock Breeding and Selection: 2nd Edition)

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27 pages, 832 KB  

Open AccessReview

Enhancing Genomic Selection in Dairy Cattle Through Artificial Intelligence: Integrating Advanced Phenotyping and Predictive Models to Advance Health, Climate Resilience, and Sustainability

by Karina Džermeikaitė, Monika Šidlauskaitė, Ramūnas Antanaitis and Lina Anskienė

Dairy 2025, 6(5), 50; https://doi.org/10.3390/dairy6050050 - 1 Sep 2025

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Abstract

The convergence of genomic selection and artificial intelligence (AI) is redefining precision breeding in dairy cattle, enabling earlier, more accurate, and multi-trait selection for health, fertility, climate resilience, and economic efficiency. This review critically examines how advanced genomic tools—such as genome-wide association studies [...] Read more.

The convergence of genomic selection and artificial intelligence (AI) is redefining precision breeding in dairy cattle, enabling earlier, more accurate, and multi-trait selection for health, fertility, climate resilience, and economic efficiency. This review critically examines how advanced genomic tools—such as genome-wide association studies (GWAS), genomic breeding values (GEBVs), machine learning (ML), and deep learning (DL) models to accelerate genetic gain for complex, low heritability traits. Key applications include improved resistance to mastitis and metabolic diseases, enhanced thermotolerance, reduced enteric methane emissions, and increased milk yield. We discuss emerging computational frameworks that combine sensor-derived phenotypes, omics datasets, and environmental data to support data-driven selection decisions. Furthermore, we address implementation challenges related to data integration, model interpretability, ethical considerations, and access in low-resource settings. By synthesizing interdisciplinary advances, this review provides a roadmap for developing AI-augmented genomic selection pipelines that support sustainable, climate-smart, and economically viable dairy systems. Full article

(This article belongs to the Topic Application of Reproductive and Genomic Biotechnologies for Livestock Breeding and Selection: 2nd Edition)

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