Special Issue "Integrative Omics Technologies and Machine Learning Approaches in Animal Production"

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

Deadline for manuscript submissions: 30 June 2022.

Special Issue Editor

Dr. Sunday Peters
E-Mail Website
Guest Editor
Department of Animal Science, Berry College, Mount Berry, GA, USA
Interests: integrative omics; machine learning; statistical genetics; animal breeding

Special Issue Information

Dear Colleagues,

Advances in molecular biology have revolutionized research in livestock production. The application of genomics, transcriptomics, metatranscriptomics, proteomics, nutrigenomics, metagenomics, and metabolomics has not only provided the opportunity to decipher the genomic architecture underlying traits of interest but also enhanced our understanding of the molecular basis of growth, reproduction, and carcass merit, as well as the role of selection and nutrition and of other environmental factors. There is also a growing interest in the use of semi- and non-parametric methods for genomic prediction, because the conventional approach of using linear regression models has been said to ignore gene–gene interactions and higher order non-linearities. In this context, machine learning approaches provide interesting alternatives for marker-based genomic selection and omics approaches.

This Special Issue invites manuscripts that apply omics technologies and those that utilize any machine learning approach in livestock production.

Dr. Sunday Peters
Guest Editor

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 papers will be 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 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

  • Genomics
  • Transcriptomics
  • Metatranscriptomics
  • Nutrigenomics
  • Proteomics
  • Metabolomics
  • Metagenomics
  • Artificial Neural Network
  • Machine Learning

Published Papers (2 papers)

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Research

Communication
Genomic Imprinting at the Porcine DIRAS3 Locus
Animals 2021, 11(5), 1315; https://doi.org/10.3390/ani11051315 - 03 May 2021
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Abstract
The epigenetic mechanisms underlying genomic imprinting include DNA methylation and monoallelic expression of genes in close proximity. Although genes imprinted in humans and mice have been widely characterized, there is a lack of detailed and comprehensive studies in livestock species including pigs. The [...] Read more.
The epigenetic mechanisms underlying genomic imprinting include DNA methylation and monoallelic expression of genes in close proximity. Although genes imprinted in humans and mice have been widely characterized, there is a lack of detailed and comprehensive studies in livestock species including pigs. The purpose of this study was to investigate a detailed methylation status and parent-of-origin-specific gene expression within the genomic region containing an underexamined porcine DIRAS3 locus. Through whole-genome bisulfite sequencing (WGBS) and RNA sequencing (RNA-seq) of porcine parthenogenetic embryos and analyses of public RNA-seq data from adult pigs, DNA methylation and monoallelic expression pattern were investigated. As a result, maternal hypermethylation at the DIRAS3 locus and hypothalamus-specific and monoallelic expression of the DIRAS3 gene were found in pigs. In conclusion, the findings from this study suggest that the presence of maternal hypermethylation, or imprints, might be maintained and related to monoallelic expression of DIRAS3 during pig development. Full article
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Article
Plasma Carboxyl-Metabolome Is Associated with Average Daily Gain Divergence in Beef Steers
Animals 2021, 11(1), 67; https://doi.org/10.3390/ani11010067 - 01 Jan 2021
Viewed by 559
Abstract
We applied an untargeted metabolomics technique to analyze the plasma carboxyl-metabolome of beef steers with divergent average daily gain (ADG). Forty-eight newly weaned Angus crossbred beef steers were fed the same total mixed ration ad libitum for 42 days. On day 42, the [...] Read more.
We applied an untargeted metabolomics technique to analyze the plasma carboxyl-metabolome of beef steers with divergent average daily gain (ADG). Forty-eight newly weaned Angus crossbred beef steers were fed the same total mixed ration ad libitum for 42 days. On day 42, the steers were divided into two groups of lowest (LF: n = 8) and highest ADG (HF: n = 8), and blood samples were obtained from the two groups for plasma preparation. Relative quantification of carboxylic-acid-containing metabolites in the plasma samples was determined using a metabolomics technique based on chemical isotope labeling liquid chromatography mass spectrometry. Metabolites that differed (fold change (FC) ≥ 1.2 or ≤ 0.83 and FDR ≤ 0.05) between LF and HF were identified using a volcano plot. Metabolite set enrichment analysis (MSEA) of the differential metabolites was done to determine the metabolic pathways or enzymes that were potentially altered. In total, 328 metabolites were identified. Volcano plot analysis revealed 43 differentially abundant metabolites; several short chain fatty acids and ketone bodies had greater abundance in HF steers. Conversely, several long chain fatty acids were greater in LF steers. Five enzymatic pathways, such as fatty acyl CoA elongation and fatty-acid CoA ligase were altered based on MSEA. This study demonstrated that beef steers with divergent ADG had altered plasma carboxyl-metabolome, which is possibly caused by altered abundances and/or activities of enzymes involved in fatty acid oxidation and biosynthesis in the liver. Full article
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