Livestock Germplasm Resources, Genetics, and Breeding

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: 25 September 2026 | Viewed by 1005

Editors


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Guest Editor
Department of Veterinary Sciences, University of Messina, Viale G. Palatucci, 98168 Messina, Italy
Interests: animal breeding; genetic improvement; genomic selection; conservation; biodiversity; gene regulation; breed traceability; coat color
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Chemical, Biological, Pharmaceutical and Environmental Sciences, University of Messina, V.le F. Stagno d’Alcontres, 98166 Messina, Italy
Interests: animal breeding; quantitative genetics; genomics; bioinformatic; biodiversity

Special Issue Information

Dear Colleagues, 

This Special Issue, “Livestock Germplasm Resources, Genetics, and Breeding”, will present a comprehensive examination of contemporary advancements in animal breeding science, emphasizing innovative methodologies, genetic research, and the integration of genomics into livestock production systems. This Special Issue will highlight cutting-edge studies aimed at enhancing economically important traits, optimizing genetic gain, and promoting sustainable and resilient breeding strategies.

Contributions will explore a spectrum of approaches—from traditional selection schemes to advanced genomic selection, marker-assisted breeding, and functional genomics—illustrating the pivotal role of molecular tools in shaping next-generation breeding programs. Through in-depth analyses and applied case studies, this Special Issue will address the challenges and opportunities inherent in modern genetic improvement, providing critical insights to increase productivity and animal health and welfare across a range of livestock species.

Dr. Enrico D’ Alessandro
Dr. Marco Tolone
Guest Editors

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Keywords

  • animal genetics
  • genomics
  • animal production
  • metagenomics
  • genome-wide association study (GWAS)
  • product quality
  • fertility
  • health
  • coat color
  • molecular traceability
  • biodiversity

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Published Papers (1 paper)

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Research

16 pages, 782 KB  
Article
A Comprehensive Analysis of the Agreement and Performance of Variant Annotation Programs in Equine Genomes
by Jillian L. Marlowe, Lauren Hughes, Eric Barrey, Tosso Leeb, Rebecca Bellone, Molly E. McCue and Sian Durward-Akhurst
Genes 2026, 17(6), 704; https://doi.org/10.3390/genes17060704 - 18 Jun 2026
Viewed by 186
Abstract
Background/Objectives: Advances in whole-genome sequencing (WGS) technology have led to the widespread adoption of WGS for investigating genetic diseases and traits in domestic animals. This has created a need for improved methods for prioritizing candidate causal variants. One way variants are prioritized is [...] Read more.
Background/Objectives: Advances in whole-genome sequencing (WGS) technology have led to the widespread adoption of WGS for investigating genetic diseases and traits in domestic animals. This has created a need for improved methods for prioritizing candidate causal variants. One way variants are prioritized is using variant annotators that predict variant effects based on their proximity to genomic features and effect on amino acid sequence. However, validation of variant annotators for domestic animal genomes is lacking. Methods: In this study, we calculated the agreement of three popular variant annotators, Ensembl Variant Effect Predictor (Ensembl-VEP), SnpEff, and ANNOVAR, across >58 million variants identified in 1065 horse genomes. Results: Comparisons showed that agreement across all three variant annotators was >90% when terminology was standardized. Terminology standardization was the most important factor affecting agreement, as agreement dropped to 0–67% when terminology was not standardized across variant annotators. Genomic context was also a major factor, as exonic, and specifically loss-of-function, variants showed lower agreement rates than intergenic variants. In addition to annotation agreement, differences in computational resource requirements were identified. ANNOVAR required ~28× more memory and ~1.5× more time than the next best tool. Conclusions: These results demonstrate that tool selection for annotating variants should not be based on a single metric; rather, a study’s needs and available computational resources should be considered when selecting the appropriate variant annotators(s) along with the standardization of terminology across annotators. These findings are a resource for guiding decisions on the use of variant annotators in domestic animals and suggest areas for improvement in the standardization of variant prioritization. Full article
(This article belongs to the Special Issue Livestock Germplasm Resources, Genetics, and Breeding)
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