Advances in Livestock Breeding: From DNA Sequencing to Selection Techniques

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal Genetics and Genomics".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 961

Special Issue Editors


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Guest Editor
Department of Animal Molecular Biology, National Research Institute of Animal Production, 1, Krakowska Street, 32-083 Balice, Poland
Interests: proteomics; gene expression; SNP; NGS; mass spectrometry

E-Mail Website
Guest Editor
Department of Animal Molecular Biology, National Research Institute of Animal Production, 1, Krakowska Street, 32-083 Balice, Poland
Interests: population genetics; species identification; SNP; STR
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Special Issue Information

Dear Colleagues,

The field of livestock breeding has undergone a transformative evolution with the integration of high-throughput sequencing and advanced selection techniques. While traditional breeding methods have been pivotal in improving desirable traits, the advent of omics technologies—such as genomics, transcriptomics, proteomics, and metabolomics—has deepened our understanding of the complex biological networks that govern animal performance, health, and reproduction. This Special Issue aims to highlight the latest advancements in livestock breeding, from DNA sequencing and SNP discovery to the functional analysis of gene expression and protein dynamics. Particular emphasis is placed on the role of proteomics in bridging the gap between genotype and phenotype, enabling more accurate selection strategies. We invite contributions that explore innovative breeding programs, biomarker discovery, multi-omics data integration, and the application of cutting-edge technologies, such as mass spectrometry, in animal science. Studies focusing on sustainable breeding practices, disease resistance, fertility, and the improvement of production traits in any species (terrestrial, birds, and pollinators) are especially welcome.

Dr. Grzegorz Smołucha
Dr. Anna Koseniuk
Guest Editors

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Keywords

  • livestock breeding
  • DNA sequencing
  • proteomics
  • genomics
  • mass spectrometry
  • biomarkers
  • genetic selection
  • multi-omics integration
  • functional genomic
  • sustainable agriculture

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Published Papers (1 paper)

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Research

14 pages, 11470 KB  
Article
Candidate Gene Identification and Genomic Prediction for Key Reproductive Traits in Yorkshire, Landrace, and Duroc Pigs
by Wenjie Hao, Wu-Sheng Sun, Zhuoshan Li, Jingbo Zhang, Lijun Shi, Hasi Chaolu, Qi Zhang, Teerath Kumar Suthar, Lixian Wang and Shu-Min Zhang
Animals 2026, 16(7), 999; https://doi.org/10.3390/ani16070999 - 24 Mar 2026
Viewed by 380
Abstract
The study analyzed ten reproductive traits in three major commercial breeds—Yorkshire, Landrace, and Duroc—raised under uniform management. Genetic parameters were estimated using a repeatability animal model in ASReml, genome-wide association studies (GWAS) were performed with 46,358 post-QC SNPs using GCTA, and genomic prediction [...] Read more.
The study analyzed ten reproductive traits in three major commercial breeds—Yorkshire, Landrace, and Duroc—raised under uniform management. Genetic parameters were estimated using a repeatability animal model in ASReml, genome-wide association studies (GWAS) were performed with 46,358 post-QC SNPs using GCTA, and genomic prediction was evaluated with GBLUP. Heritability estimates were low to moderate, with gestation length (GL) highest (0.33–0.41). GWAS identified significant loci across breeds: in Yorkshire, 37 genome-wide significant SNPs across 17 SSCs for seven traits; in Landrace, 16 SNPs for TNB and one for NBW; and in Duroc, 31 SNPs across 12 SSCs (predominantly for TNB). Among these SNPs, CNC10042060, CNC10160995, and CNCB10003799 were consistently associated with TNB in both Yorkshire and Duroc pigs. Additionally, five SNPs, CNC10012965, CNC10042060, CNC10120451, CNCB10003799, and CNCB10007759, showed significant associations with NBW in Yorkshire and Landrace pigs. Candidate genes mapped within ±1 Mb of significant SNPs were enriched for biologically plausible pathways. Genomic prediction accuracies ranged from low to high depending on trait and breed, such as reaching 0.68 for GL in 39 Yorkshire and 0.59 in Landrace. These results delineate shared and breed-specific genetic architectures, provide actionable markers and candidate genes, and can accelerate genetic gains in commercial breeding programs. Full article
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