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Animals
Special Issues
Livestock Genetic Evaluation and Selection
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Livestock Genetic Evaluation and Selection

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 3149

Special Issue Editors

Dr. Heather Huson

E-Mail Website
Guest Editor
Department of Animal Science, Cornell University, Ithaca, NY, USA
Interests: genetic improvement of animal health and production; dairy cattle management and genetic evaluations; population structure and adaptation; genomic tool development; wildlife and indigenous population conservation; canine genetics
Special Issues, Collections and Topics in MDPI journals
Dr. Srikanth Krishnamoorthy

E-Mail Website
Guest Editor
Department of Animal Science, Cornell University, Ithaca, NY, USA
Interests: livestock and canine genomics; multi omics data analysis; genomic prediction; genetic diversity; environmental adaptation genetics

Special Issue Information

Dear Colleagues,

Livestock genetic evaluation and genomic selection have transformed animal agriculture by enhancing productivity, health, and environmental resilience. The availability of low-cost genomic technologies combined with advances in genomic selection methods have accelerated genetic improvement, enabling the precise identification of animals with desired traits such as higher milk yield, disease resistance, and feed efficiency, allowing breeders to make informed and accurate selection decisions. Genomics also enables genetic evaluation for novel traits such as feed efficiency, hoof health, methane emission, and heat tolerance when only limited phenotypes are available. The integration of multi omics data in genomic prediction, and  the use of novel statistical methods such as machine learning and deep learning, could improve genomic prediction accuracy. There is also an increasing need for genomic evaluation for novel phenotypes such as methane emissions, environmental adaptation, and resilience.

The aim of this Special Issue is to highlight advances in genomic evaluation and selection for novel phenotypes, use of new statistical methods, integration of muti-omics for genomic prediction, and improvements in evaluations and selection in crossbred cattle in underdeveloped countries. These topics fall within the scope of the journal as they deal with breeding and genetic selection and use of genomics. 

Reviews and research papers in the areas listed below are welcome.  

  • Development and optimization of genomic selection methods for production, health, and resilience traits.
  • Development and optimization of genomic selection for crossbred and indigenous cattle.
  • Improvements in genetic evaluation and selection in underdeveloped countries.
  • Use of advanced statistical approaches, including machine learning, to enhance prediction accuracy.
  • Integration of genomics, transcriptomics, proteomics, and metabolomics to identify biomarkers and improve selection.
  • Genetic evaluation of heat tolerance, disease resistance, and adaptation to climate change.
  • Traits related to environmental sustainability, such as methane emissions and feed efficiency.
  • Identification and genomic evaluation of emerging phenotypes, such as behavior, welfare traits, and reproductive efficiency.

Dr. Heather Huson
Dr. Srikanth Krishnamoorthy
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

  • genomic selection
  • genetic selection
  • gEBV
  • genetic evaluations
  • gBLUP
  • machine learning

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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23 pages, 2383 KB  
Article
A New Family-Based Approach for Detecting Allele-Specific Expression and for Mapping Possible eQTLs
by Maher Alnajjar, Zsófia Fekete, Tibor Nagy, Zoltán Német, Agshin Sakif, Nóra Ninausz, Péter Fehér, Viktor Stéger and Endre Barta
Animals 2025, 15(18), 2766; https://doi.org/10.3390/ani15182766 - 22 Sep 2025
Viewed by 494
Abstract
Allele-specific expression (ASE) reflects the unequal expression of the parental alleles and can imply functional variants in cis-regulatory elements. The conventional ASE detection methods often depend on the presence of heterozygous variants in transcripts or sequencing a large number of individuals, both of [...] Read more.
Allele-specific expression (ASE) reflects the unequal expression of the parental alleles and can imply functional variants in cis-regulatory elements. The conventional ASE detection methods often depend on the presence of heterozygous variants in transcripts or sequencing a large number of individuals, both of which are often limited. In this study, we present a family-based strategy for detecting ASE and potential cis-regulatory elements utilizing both RNA-seq and whole-genome sequencing (WGS) from a pedigree. Using a rabbit family consisting of two divergent parents and their eight offspring, we identified 913 ASE genes by analyzing inheritance patterns of gene expression levels. Expression was classified into three levels—high, medium, and low—and used to define seven distinct expression groups across the family (e.g., H_L: high in the mother, low in the father, and intermediate in the offspring). Many ASE genes lacked heterozygous exonic variants, and inference was achieved via RNA read count patterns. We also pinpointed conserved transcription factor binding sites (TFBS) with sequence variants showing similar inherited genotypic patterns (e.g., AAxBB), suggesting their regulatory roles as eQTLs. Differential gene expression (DEG) analysis between the parents highlighted some candidate genes related to meat production and quality traits. Our findings show that the family-based method using RNA-seq and WGS data is promising for exploring ASE and mapping possible eQTLs. Full article
(This article belongs to the Special Issue Livestock Genetic Evaluation and Selection)
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17 pages, 3096 KB  
Article
Local Climate Adaptation in Chinese Indigenous Pig Genomes
by Yuqiang Liu, Yang Xu, Guangzhen Li, Wondossen Ayalew, Zhanming Zhong and Zhe Zhang
Animals 2025, 15(16), 2412; https://doi.org/10.3390/ani15162412 - 18 Aug 2025
Viewed by 676
Abstract
Local adaptation allows animal populations to persist in diverse and changing environments, yet its genomic underpinnings remain poorly characterized in livestock. Chinese indigenous pigs, renowned for their rich phenotypic and ecological diversity, offer a powerful model for investigating environmental adaptation. Here, we integrated [...] Read more.
Local adaptation allows animal populations to persist in diverse and changing environments, yet its genomic underpinnings remain poorly characterized in livestock. Chinese indigenous pigs, renowned for their rich phenotypic and ecological diversity, offer a powerful model for investigating environmental adaptation. Here, we integrated whole-genome resequencing data, environmental variables, genotype–environment association (GEA) analyses, and functional annotation to explore the adaptive genomic landscape of 46 native pig breeds across China. Based on 578 individuals and 17.7 million SNPs, we performed genome-wide GEA using latent factor mixed models (LFMMs), identifying 8644 SNPs significantly associated with environmental factors, including 310 linked to precipitation in the wettest quarter (BIO16). Redundancy analysis (RDA) and gradient forest modeling identified BIO16 as a major environmental driver of genomic variation. Functional annotation of BIO16-associated SNPs revealed significant enrichment in regulatory elements and genes highly expressed in the lung, spleen, hypothalamus, and intestine, implicating immune and metabolic pathways in local adaptation. Among the candidate loci, MS4A7 exhibited strong association signals, population differentiation, and tissue-specific regulation, suggesting a role in precipitation-mediated adaptation. This work enhances our understanding of livestock adaptation and informs climate-resilient conservation and breeding strategies. Full article
(This article belongs to the Special Issue Livestock Genetic Evaluation and Selection)
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24 pages, 8294 KB  
Article
The Effect of Continuous Selection in KiwiCross® Composite Breed on Breed Ancestry and Productivity Performance
by Mohd Jaafar, Bevin Harris and Heather J. Huson
Animals 2025, 15(2), 175; https://doi.org/10.3390/ani15020175 - 10 Jan 2025
Viewed by 1474
Abstract
Composite crosses result from the mating of two or more distinct cattle breeds. Breeding performance may improve rapidly using a well-organized composite breeding system and a clear selection index. The KiwiCross® is a popular composite cross in New Zealand, combining Holstein-Friesian (high [...] Read more.
Composite crosses result from the mating of two or more distinct cattle breeds. Breeding performance may improve rapidly using a well-organized composite breeding system and a clear selection index. The KiwiCross® is a popular composite cross in New Zealand, combining Holstein-Friesian (high milk production) and Jersey (high milk fat). Production efficiency (PR), a key selection index, is calculated by dividing milk solids produced by mature live weight. Over decades of genetic improvement, KiwiCross® increased milk production significantly. We hypothesized that certain genomic regions from Holstein-Friesian or Jersey breeds were preserved due to artificial selection based on PR. Analysis of genomic regions using XP-EHH, hapFLK, and ROH haplotype statistics revealed selection signatures on BTA 7 and 20 in both high- and low-performance animals, with distinct regions linked to Holstein-Friesian and Jersey ancestry. Our findings suggest that selection acted on different genomic regions across generations and that preserving key ancestry-specific haplotypes is crucial for maintaining performance in composite breeds. Breeders must recognize that selection for specific traits can alter allele frequencies and lead to the loss of beneficial breed-specific haplotypes over time. Full article
(This article belongs to the Special Issue Livestock Genetic Evaluation and Selection)
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