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Animals
Special Issues
Molecular Markers and Genomic Selection in Farm Animal Improvement
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Molecular Markers and Genomic Selection in Farm Animal Improvement

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 2025 | Viewed by 306

Special Issue Editors

Dr. Xubin Lu

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Guest Editor
College of Animal Science and Technology, Yangzhou University, Yangzhou 225009, China
Interests: quantitative genetics; statistical genomics; genome-wide association analysis; multi-omics research; molecular regulatory network
Dr. Qingbo Zhao

E-Mail
Guest Editor
College of Animal Science & Technology, Nanjing Agricultural University, Nanjing 210095, China
Interests: population genetics; quantitative genetics; statistical genomics; conservation genetics; animal breeding

Special Issue Information

Dear Colleagues,

The genetic improvement of farm animals plays a pivotal role in enhancing productivity, disease resistance, and overall welfare. With advancements in genomic technologies, molecular markers, and genomic selection have become powerful tools for accelerating breeding programs and improving traits of economic and functional importance in livestock. These tools enable the more precise selection of desirable traits, including growth rate, milk yield, disease resistance, and reproductive performance.

This Special Issue invites original research papers to contribute that explore the application of molecular markers and genomic selection in farm animal improvement. Topics may include the identification and validation of genetic markers for key traits, the development of genomic prediction models, the integration of genomic data into breeding programs, and the role of gene editing technologies in livestock improvement. We aim to highlight the latest advancements and provide insights into how genomic approaches can contribute to sustainable and efficient livestock production in the face of changing environmental conditions and consumer demands.

Dr. Xubin Lu
Dr. Qingbo Zhao
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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • molecular markers
  • genomic selection
  • genomic prediction model
  • livestock breeding
  • farm animal genetics

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Published Papers (1 paper)

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Research

17 pages, 1169 KiB  
Article
Integrating Significant SNPs Identified by GWAS for Genomic Prediction of the Number of Ribs and Carcass Length in Suhuai Pigs
by Kaiyue Liu, Yanzhen Yin, Binbin Wang, Chenxi Liu, Wuduo Zhou, Peipei Niu, Ruihua Huang, Pinghua Li and Qingbo Zhao
Animals 2025, 15(3), 412; https://doi.org/10.3390/ani15030412 - 2 Feb 2025
Viewed by 186
Abstract
The number of ribs (NRs) and the carcass length (CL) are important economic traits. The traits are usually measured after slaughter. To improve the prediction performance of genomic selection (GS) for NRs and CL, one strategy is to integrate the significant loci identified [...] Read more.
The number of ribs (NRs) and the carcass length (CL) are important economic traits. The traits are usually measured after slaughter. To improve the prediction performance of genomic selection (GS) for NRs and CL, one strategy is to integrate the significant loci identified from whole-genome sequencing (WGS) data by genome-wide association study (GWAS) into the genomic prediction (GP) model. This study investigated the GP of different genomic best linear unbiased prediction (GBLUP) and Bayesian models using chip genotype data, imputed WGS (iWGS) data and modeling significant single-nucleotide polymorphisms (SNPs) in different ways for the GP of NRs and CL in the Suhuai pig population. The prediction accuracy, bias and running time of 15 different GP models were evaluated by 10-fold cross-validation. The prediction accuracy of GBLUP using chip data for NRs and CL was 0.314 ± 0.022 and 0.194 ± 0.040, respectively. For NRs, based on the iWGS data, treating the most significant SNP as fixed effects in the GBLUP model had the highest predictive performance, with a prediction accuracy of 0.528 ± 0.023. For CL, based on the chip data, the model that added all the significant SNPs identified by imputed data by GWAS into the multi-trait GBLUP as the second random additive effect was the highest predictive performance, with a prediction accuracy of 0.305 ± 0.027. This study provides insights into optimizing GP models for small populations with phenotypes that are difficult to measure. Full article
(This article belongs to the Special Issue Molecular Markers and Genomic Selection in Farm Animal Improvement)
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