Use of Longitudinal Information, Imaging, and Sensor Data in Genetic Evaluation

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 1622

Special Issue Editors


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Guest Editor
Université Paris Saclay, INRAE, AgroParisTech, GABI, Domaine de Vilvert, 78350 Jouy-en-Josas, France
Interests: genetic evaluation; genomic prediction; statistical genomics; environmental effects; linear models; variance components

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Guest Editor
Department of Animal Sciences, Purdue University, 270 S Russell St, West Lafayette, IN 47970, USA
Interests: livestock genomics; quantitative genetics; physiological genomics; behavior; welfare; resilience; small ruminants; cattle; pigs; environmental efficiency
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Guest Editor
Department of Animal Science, Michigan State University, 474 S Shaw Ln, East Lansing, MI 48824, USA
Interests: genetic evaluation; animal husbandry; environmental effects; breeding program; cattle

Special Issue Information

Dear Colleagues,

Genetic and genomic selection have been widely adopted by most livestock production systems around the world, which have enabled substantial improvement in animal production efficiency. The second half of the 20th century was marked by a great volume of research and improvements of the statistical methods and applications of genetic evaluation for the selection of individuals within a breeding program. Thanks to the fast advances in molecular technology and computational capacity in both storing and processing data, the 21st century brought the era of genomics to agricultural production systems. Currently, most livestock breeding programs routinely incorporate genomic data for predicting the genetic merit of individual animals for a wide range of traits.

One of the most pressing challenges to the agricultural industry is to further improve production efficiency, animal welfare, and the overall sustainability of the animal production system, in order to provide nutritious food for a rapidly-growing population in an environment that is being disrupted by climate change and limited agricultural lands. In the face of such challenges, researchers are continuously moving their efforts to develop models for genetic evaluation that integrate a wide variety of omics data, environmental descriptors, and novel phenotypes generated by precision farming technologies. All these data sources can be highly valuable when applied to breeding programs, including in the prediction of genomic breeding values and comprehension of the underlying biology that regulates phenotypic expression of key traits of interest. Moreover, a large amount of historical data has been accumulated in many livestock production systems, enabling the comprehensive study of longitudinal patterns, and their association to a series of effects.

This special issue of Animals – Use of longitudinal information, imaging, and sensor data in genetic evaluation – intends to bring the public’s attention to complementary and innovative approaches to the use of novel data available in livestock production. This includes but it is not limited to: applications of environmental and climate data in genetic evaluation or phenotypic prediction; longitudinal population studies; incorporation of multi-omics information for genomic or phenotypic prediction; definition of novel traits and breeding goal based on high-throughput phenotypes; methods and models to process and analyze longitudinal, imaging and sensor data; and, economic or social impacts of novel breeding and phenotyping technologies. Submitted manuscripts should emphasize the uniqueness of their research in terms of methodology, data, population and/or phenotypes, as well as both the strengths and weaknesses of their study or data, with interpretation of the obtained results. We acknowledge as well that negative results are important outcomes in scientific literature, and authors with such results should be encouraged to submit their manuscripts.

Dr. Beatriz C.D. Cuyabano
Dr. Luiz F. Brito
Dr. Gabriel Rovere
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

  • environmental effects
  • heat stress
  • genotype-by-environment interactions
  • animal welfare
  • resilience traits
  • longitudinal traits
  • sustainable production
  • livestock behavior
  • high-throughput phenotyping
  • quantitative genomics

Published Papers (1 paper)

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Research

24 pages, 2698 KiB  
Article
Heteroscedastic Reaction Norm Models Improve the Assessment of Genotype by Environment Interaction for Growth, Reproductive, and Visual Score Traits in Nellore Cattle
by Ivan Carvalho Filho, Delvan A. Silva, Caio S. Teixeira, Thales L. Silva, Lucio F. M. Mota, Lucia G. Albuquerque and Roberto Carvalheiro
Animals 2022, 12(19), 2613; https://doi.org/10.3390/ani12192613 - 29 Sep 2022
Cited by 2 | Viewed by 1391
Abstract
The assessment of the presence of genotype by environment interaction (GxE) in beef cattle is very important in tropical countries with diverse climatic conditions and production systems. The present study aimed to assess the presence of GxE by using different reaction norm models [...] Read more.
The assessment of the presence of genotype by environment interaction (GxE) in beef cattle is very important in tropical countries with diverse climatic conditions and production systems. The present study aimed to assess the presence of GxE by using different reaction norm models for eleven traits related to growth, reproduction, and visual score in Nellore cattle. We studied five reaction norm models (RNM), fitting a linear model considering homoscedastic residual variance (RNM_homo), and four models considering heteroskedasticity, being linear (RNM_hete), quadratic (RNM_quad), linear spline (RNM_l-l), and quadratic spline (RNM_q-q). There was the presence of GxE for age at first calving (AFC), scrotal circumference (SC), weaning to yearling weight gain (WYG), and yearling weight (YW). The best models were RNM_l-l for YW and RNM_q-q for AFC, SC, and WYG. The heritability estimates for RNM_l-l ranged from 0.07 to 0.20, 0.42 to 0.61, 0.24 to 0.42, and 0.47 to 0.63 for AFC, SC, WYG, and YW, respectively. The heteroskedasticity in reaction norm models improves the assessment of the presence of GxE for YW, WYG, AFC, and SC. Additionally, the trajectories of reaction norms for these traits seem to be affected by a non-linear component, and selecting robust animals for these traits is an alternative to increase production and reduce environmental sensitivity. Full article
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