Special Issue "Modeling Genotype by Environment Interaction for Precision Farming and Improved Animal Welfare"

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

Deadline for manuscript submissions: 31 December 2021.

Special Issue Editors

Prof. Francesco Tiezzi
E-Mail Website
Guest Editor
Department of Animal Science, North Carolina State University, Raleigh, NC 27695, USA
Interests: genomic selection; genotyping strategies; genotype by environment interaction; meat quality; selection index
Prof. Luiz F. Brito
E-Mail Website
Guest Editor
Department of Animal Sciences, Purdue University, West Lafayette, IN 47907, USA
Interests: livestock genomics; quantitative genetics; physiological genomics; behavior; welfare; resilience; small ruminants; cattle; pigs; environmental efficiency
Prof. Breno Fragomeni
E-Mail Website
Guest Editor
Department of Animal Science, University of Connecticut, Storrs, CT 06269, USA
Interests: genomic selection; genotype-by-environment interaction; heat stress; genomic prediction; genetics of disease resistance

Special Issue Information

Dear Colleagues,

Livestock genetic improvement is experiencing a new phase of increased relevance, where novel traits, sophisticated statistical methods and high-throughput technologies are constantly being proposed or refined. Such advancements are resulting in faster rates of genetic progress compared to the pre-genomics era. The large majority of livestock breeding programs have primarily focused on productive traits, but more recently, worldwide selection indexes are being refined to incorporate indicators of reproductive performance, animal resilience, adaptation to changing environments, and health traits. Meanwhile, agriculture in general is moving to data-based decision making, where a wealth of data and heavy use of computational tools are employed every day for planning, monitoring, and managing livestock production and breeding.

Large datasets were necessary for performing genetic improvement of livestock before they became popular for decision making on other contexts of production. Now, genetic improvement is moving towards the incorporation of large and comprehensive datasets, that include phenotypic, genomic, physiological and environmental variables into statistical genomic models. This expansion in tools available happens contemporarily to the raising importance of welfare traits as breeding goals, driven by market demand and its increased economic importance (e.g. heat stress tolerance). The evaluation of animal welfare involves a complete assessment of the animal’s physiological, behavioral, physical, and emotional state. Therefore, animal welfare cannot be reduced to a single trait, but is composed of a wide spectrum of variables, which are probably determined by interactions between the genotype and environmental effects. Precision livestock farming and selection for animal welfare show an inherent advantage of including genotype by environment interactions. This involves scouting for new data sources (e.g. sensors), testing or refining statistical models (e.g. machine learning), unravelling genomic regions associated with such interactions, and engaging livestock industry stakeholders about the potential of these new methods and approaches (e.g. interactive selection index composition). 

We invite original research papers, literature reviews and technical notes that address the topic of selection for novel and innovative traits incorporating the modelling of genotype by environment interactions. List of topics includes, but is not limited to: use of sensors in measuring phenotypes or determining condition, selection and genomic basis of tolerance to thermal stress, modelling of longitudinal data, behavioral genomics, and genetic by environment interaction in the determination of relevant breeding goals and product quality traits. Papers having any livestock species as subject are welcome. 

Prof. Francesco Tiezzi
Prof. Luiz F. Brito
Prof. Breno Fragomeni
Guest Editors

Manuscript Submission Information

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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 monthly 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 1800 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
  • Genotype by environment interaction
  • Heat tolerance
  • Animal welfare
  • Precision livestock farming
  • Animal resilience
  • Longitudinal data

Published Papers (2 papers)

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Research

Article
Use of Principal Component Analysis to Combine Genetic Merit for Heat Stress and for Fat and Protein Yield in Spanish Autochthonous Dairy Goat Breeds
Animals 2021, 11(3), 736; https://doi.org/10.3390/ani11030736 - 08 Mar 2021
Cited by 1 | Viewed by 473
Abstract
We studied the effect of the Temperature Humidity Index (THI) (i.e., the average of temperature and relative humidity registered at meteorological stations) closest to the farms taken during the test day (TD), for total daily protein and fat yields (fpy) of the three [...] Read more.
We studied the effect of the Temperature Humidity Index (THI) (i.e., the average of temperature and relative humidity registered at meteorological stations) closest to the farms taken during the test day (TD), for total daily protein and fat yields (fpy) of the three main Spanish dairy goats. The data were from Florida (11,244 animals and 126,825 TD), Malagueña (12,215 animals and 141,856 TD) and Murciano Granadina (5162 animals and 62,834 TD) breeding programs and were studied by different linear models to estimate the nature of the fpy response throughout the THI and the weeks of lactation (Days in Milk, DIM) trajectories. The results showed an antagonism between THI and DIM, with a marked depression in the fpy level in animals kept in the hot zone of the THI values (THI > 25) compared with those in the cold zone (THI ≤ 16), with a negative impact equivalent to production of 13 to 30 days. We used a Reaction Norm model (RN), including THI and DIM as fixed covariates and a Test Day Model (TDM), to estimate the genetic (co)variance components. The heritability and genetic correlations estimated with RN and TDM showed a decreased pattern along the scale of THI and DIM, with slight differences between breeds, meaning that there was significant genetic variability in the animal’s ability to react to different levels of THI, which is not constant throughout the DIM, showing the existence of genotype-environment interaction. The breeding values (BV) of all animals for each level of THI and DIM were subject to a principal component analysis, and the results showed that 89 to 98% of the variance between the BV was explained by the two first eigenvalues. The standardized BV were weighted with the corresponding eigenvector coefficients to construct an index that showed, in a single indicator, the most complete expression of the existing genetic variability in the animals’ ability to produce fpy along the trajectories of THI and DIM. This new option will make it easier to select animals which are more productive, and with better adaptability to heat stress, as well as enabling us to exploit genetic variations in the form of the response to heat stress to be adapted to different production systems. Full article
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Article
Selection for Test-Day Milk Yield and Thermotolerance in Brazilian Holstein Cattle
Animals 2021, 11(1), 128; https://doi.org/10.3390/ani11010128 - 08 Jan 2021
Cited by 1 | Viewed by 564
Abstract
Intense selection for milk yield has increased environmental sensitivity in animals, and currently, heat stress is an expensive problem in dairy farming. The objectives were to identify the best model for characterizing environmental sensitivity in Holstein cattle, using the test-day milk yield (TDMY) [...] Read more.
Intense selection for milk yield has increased environmental sensitivity in animals, and currently, heat stress is an expensive problem in dairy farming. The objectives were to identify the best model for characterizing environmental sensitivity in Holstein cattle, using the test-day milk yield (TDMY) combined with the temperature–humidity index (THI), and identify sires genetically superior for heat-stress (HS) tolerance and milk yield, through random regression. The data comprised 94,549 TDMYs of 11,294 first-parity Holstein cows in Brazil, collected from 1997 to 2013. The yield data were fitted to Legendre orthogonal polynomials, linear splines and the Wilmink function. The THI (the average of two days before the dairy control) was used as an environmental gradient. An animal model that fitted production using a Legendre polynomials of quartic order for the days in milk and quadratic equations for the THI presented a better quality of fit (Akaike’s information criterion (AIC) and Bayesian information criterion (BIC)). The Spearman correlation coefficient of greatest impact was 0.54, between the top 1% for TDMY and top 1% for HS. Only 9% of the sires showed plasticity and an aptitude for joint selection. Thus, despite the small population fraction allowed for joint selection, sufficient genetic variability for selecting more resilient sires was found, which promoted concomitant genetic gains in milk yield and thermotolerance. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Genotype by environment interaction for test-day milk yield in sheep recorded in farmers’ field and at breeding stations in Ethiopia, by stage of lactation and various proportions of Awassi

W. G. Haile1,2, *, G. Klemetsdal1, S. Banerjee3, A. Ayele4, T. Mestawet2, and T. Ådnøy1

1. Department of Animal and Aquacultural Sciences, Norwegian University of Life Sciences, P.O. Box 5003, N-1432, Norway.

2. School of Animal and Range Sciences, College of Agriculture, Hawassa University, P.O. Box 5, Hawassa, Ethiopia.

3. College of Agricultural Sciences and Technology, Mansarovar Global University (Mansarovar Group of Institutions), Bhopal, India.

4. Debre-Berhan agricultural research centre (DBARC), Agricultural research institute, Amhara regional state, Debre-Berhan, Ethiopia.

*Correspondence: [email protected] or [email protected]

Abstract: Genotype by environment (G x E) interactions were evaluated by studying contrasts between test-day milk yield (TDMY) in breeding centres’ environment (BE) compared to farmers’ environment (FE), for combinations of similar breed proportions of Awassi and stages of lactation. A total of 1506 TDMY records from 326 ewes were analysed: The records were made at different stages of lactation and parities, from the two environments during 2015 to 2017, with ewes having the sex of their lambs recorded. To be able to get information from a limited data set, a univariate repeatability model was fitted within each environment with Legendre polynomial (LP) coefficients (3rd order) for both days in milk (DIM) and % Awassi describing fitted TDMY planes for the two environments. Over a 120 DIM, none of the genetic groups (based on % Awassi) showed significant differences in estimated contrasts for average TDMY between the two environments. This implies that genetic superiority at breeding centres will in large be realised in the farmers’ environment. With the lower % Awassi groups a significant TDMY increase was found for the stations’ environments, but not for the highest, >50 - 75% Awassi, genetic group. This G x E interaction implies that it is the high % Awassi (>50 - 75%) ewes that appear to be robust. The significant interaction in early lactation, being mostly physiological, will be avoided for most animals with the current regime for dissemination of rams that are either 50% or 75% Awassi.

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