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Animals
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Advances in Genetics and Genomics of Pig Production
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Advances in Genetics and Genomics of Pig Production

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Pigs".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 3737

Special Issue Editors

Prof. Dr. Valentina Bonfatti

E-Mail Website
Guest Editor
Department of Comparative Biomedicine and Food Science (BCA), University of Padova, Agripolis, Viale dell’Università 16, 35020 Legnaro, Padova, Italy
Interests: animal breeding and genetics; genomic selection; high-throughput phenotyping; pigs, dairy cows; milk quality; pork quality; health traits
Prof. Dr. Luca Fontanesi

E-Mail Website
Guest Editor
Department of Agricultural and Food Sciences, University of Bologna, Viale Fanin 46, 40127 Bologna, Italy
Interests: livestock genomics; livestock phenomics; whole-genome sequencing; genome-wide association studies; pig genetics and breeding; conservation of animal genetic resources
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Pig genetic improvement has rapidly progressed over recent decades, moving through various levels of technology utilization. Over time, breeding goals have expanded from a sole focus on physical appearance, feed efficiency, lean % and growth to today’s breeding goals, which include lifetime reproduction, robustness, resilience and meat quality. Over the past few decades, there has been a rapid development of high-throughput genome analysis methods, including next-generation sequencing (NGS) and single-nucleotide polymorphism genotyping. Advances in DNA technology have substantially increased opportunities for the implementation of genomic selection in pigs, leading to the development of fast, cost-effective, and more accurate methods for the implementation of breeding programs. The focus will remain on identifying relevant new phenotypes and implementing tools to measure traits effectively. For this Special Issue, original research manuscripts covering all aspects of pig genetics and genomics are welcome, in particular those with a focus on quantitative genetics of new phenotypes, genomic selection, breeding programs, gene polymorphisms, quantitative trait loci mapping, identification of causative mutations affecting economically relevant traits, and the exploitation of pig genetic resources.

Prof. Dr. Valentina Bonfatti
Prof. Dr. Luca Fontanesi
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

  • genetic improvement
  • animal breeding
  • genomic selection
  • genetic variability
  • pig production
  • phenomics
  • high-throughput phenotyping
  • pork quality
  • health
  • reproduction
  • feed efficiency
  • growth, disease resistance
  • QTL

Published Papers (2 papers)

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Research

14 pages, 730 KiB  
Article
Case Study on Increasing Breeding Value Estimation Reliability of Reproductive Traits in Serbian Highly Prolific Large White and Landrace Sows
by Nenad Stojiljković, Dragan Radojković, Zoran Luković, Marija Gogić, Čedomir Radović, Mladen Popovac and Dubravko Škorput
Animals 2022, 12(19), 2688; https://doi.org/10.3390/ani12192688 - 06 Oct 2022
Cited by 1 | Viewed by 1668
Abstract
This study investigated the influence of the degree of connectedness on the reliability of the estimated breeding values (EBVs). The focal trait in the study was the number of piglets born alive (NBA) from sows of the highly prolific Large White and Landrace [...] Read more.
This study investigated the influence of the degree of connectedness on the reliability of the estimated breeding values (EBVs). The focal trait in the study was the number of piglets born alive (NBA) from sows of the highly prolific Large White and Landrace sows. An analysis included total of 58,043 farrowing’s during the 2008–2020 period. BLUP procedure was used to estimate the breeding values for NBA for the three herds separately and after merging all three herds into one herd. The model for EBV estimation included the following fixed factors: parity, genotype, seasons, litter sire, herds, sow age at farrowing, weaning-conception interval, length of previous lactation, and the following random effects: common litter environment, permanent litter environment, and direct additive genetic effect of animal. Heritability values for NBA ranged from 0.048 to 0.097, depending on the data included in the analysis. The connectedness between herds was analysed using the connectedness rating (CR) and the gene flow (GF) methods. CR among the observed herds ranged from 0.245 to 0.994%, depending on the data included. The exchange of genetic material between all three herds was determined using GF method. The high degree of connectedness determined by the CR and GF method had a strong effect on EBV reliability. The average EBV reliability ranged from 0.520 to 0.867, depending on the data included. The increase in average reliability was observed in both cases when the data were added, both in the analysis of average reliability for purebred animals and when crossbreeds were added, where an increase in this value was also observed. The increase in average EBV reliability is a consequence of the greater amount of information included in the joint evaluation. In conclusion, we believe that our research will improve EBV reliability and help in further selection work in the Republic of Serbia. Full article
(This article belongs to the Special Issue Advances in Genetics and Genomics of Pig Production)
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13 pages, 308 KiB  
Article
Infrared Predictions Are a Valuable Alternative to Actual Measures of Dry-Cured Ham Weight Loss in the Training of Genome-Enabled Prediction Models
by Valentina Bonfatti, Sara Faggion, Elena Boschi and Paolo Carnier
Animals 2022, 12(7), 814; https://doi.org/10.3390/ani12070814 - 23 Mar 2022
Viewed by 1466
Abstract
Selection to reduce ham weight losses during dry-curing (WL) requires individual traceability of hams throughout dry-curing, with high phenotyping costs and long generation intervals. Infrared spectroscopy enables cost-effective, high-throughput phenotyping for WL 24 h after slaughter. Direct genomic values (DGV) of crossbred pigs [...] Read more.
Selection to reduce ham weight losses during dry-curing (WL) requires individual traceability of hams throughout dry-curing, with high phenotyping costs and long generation intervals. Infrared spectroscopy enables cost-effective, high-throughput phenotyping for WL 24 h after slaughter. Direct genomic values (DGV) of crossbred pigs and their purebred sires were estimated, for observed (OB) and infrared-predicted WL (IR), through models developed from 640 and 956 crossbred pigs, respectively. Five Bayesian models and two pseudo-phenotypes (estimated breeding value, EBV, and adjusted phenotype) were tested in random cross-validation and leave-one-family-out validation. The use of EBV as pseudo-phenotypes resulted in the highest accuracies. Accuracies in leave-one-family-out validation were much lower than those obtained in random cross-validation but still satisfactory and very similar for both traits. For sires in the leave-one-family-out validation scenario, the correlation between the DGV for IR and EBV for OB was slightly lower (0.32) than the correlation between the DGV for OB and EBV for OB (0.38). While genomic prediction of OB and IR can be equally suggested to be incorporated in future selection programs aiming at reducing WL, the use of IR enables an early, cost-effective phenotyping, favoring the construction of larger reference populations, with accuracies comparable to those achievable using OB phenotype. Full article
(This article belongs to the Special Issue Advances in Genetics and Genomics of Pig Production)
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