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Special Issue "Effect of Genetic and Nongenetic Factors on Functional and Milk Production Traits in Livestock"

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

Deadline for manuscript submissions: closed (25 June 2023) | Viewed by 5781

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Special Issue Editors

Dr. Mehdi Bohlouli

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Guest Editor

Institute of Animal Breeding and Domestic Animal Genetics, Justus-Liebig-Universität Gießen, Giessen, Germany
Interests: quantitative genetics; genetics of heat stress; genomic selection; genome-wide association study; genotype x environment interaction

Dr. Katharina May

E-Mail Website
Guest Editor

Institute of Animal Breeding and Domestic Animal Genetics, Justus-Liebig-Universität Gießen, Giessen, Germany
Interests: bovine health; genome-wide association study; genetics of diseases; infectious diseases; milk indicator traits; quantitative genetics

Special Issue Information

Dear Colleagues,

Over the last several decades, intensive genetic selection for increased milk yield has led to health and fertility problems, since functional traits such as health, longevity and fertility have unfavorable genetic relationships with production traits. In addition, the environment in which dairy farming is practiced varies considerably. Accordingly, susceptibility to environmental challenges such as heat stress and infectious diseases has also been gaining in importance in animal breeding. More importantly, genotype × environment interaction exists when the capacity to alter the phenotype in response to changes in the environment differs among animals.

Understanding the nature of the genetic associations between production, health and fertility traits considering nongenetic factors (e.g., production systems, regions and weather conditions) is essential to optimize the genetic selection in livestock. Several phenotypes derived from milk (e.g., somatic cell count, casein, lactose, β-hydroxybutyrate, and saturated and unsaturated fatty acids) are very useful as indicator traits to improve functional traits. On the other hand, recent advancements in genomic tools offer new opportunities for animal breeders to incorporate functional traits along with milk production traits. In the context of genomic studies, areas fruitful for genetic improvement of dairy productivity also include genome-wide association studies (GWASs) and post-GWAS analyses with a growing emphasis on the role of gene × environment interaction. Such studies identify genomic regions and candidate genes for functional and milk production traits.

This Special Issue aims to present original research (analyzing field data or simulation studies) or reviews related to genetic and environmental factors affecting livestock performance, with particular focus on health and milk production traits.

It is a great pleasure to invite you to contribute to this Special Issue.

Dr. Mehdi Bohlouli
Dr. Katharina May
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.

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 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

candidate gene
disease
farm management
functional traits
genomic region
genomic selection
animal health
milk production
cattle
goat
sheep

Published Papers (5 papers)

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Research

Open AccessArticle

CSN1S1 and LALBA Polymorphisms and Other Factors Influencing Yield, Composition, Somatic Cell Score, and Technological Properties of Cow’s Milk

and

Animals 2023, 13(13), 2079; https://doi.org/10.3390/ani13132079 - 23 Jun 2023

Viewed by 629

Abstract

We evaluated the influence of CSN1S1 and LALBA polymorphisms on cow’s milk yield and quality. The analysis was done on Czech Simmental and Holstein cows. Non-genetic factors were included as well. CSN1S1 did not influence the milk performance in the first lactation. In the second lactation, cows with the BB genotype had significantly higher milk, protein, and fat yields than BC. The differences between LALBA genotypes were non-significant in the first lactation, while in the second lactation, the fat percentage was significantly higher in BB than in AB. The farm significantly influenced milk, protein, and fat yields in both the first and second lactations and fat percentage in the first lactation. The effect of CSN1S1 and LALBA genotypes on the milk technological quality was non-significant. Breed did not influence any of the evaluated technological traits and SCS. The ethanol test was not influenced by farm, season, lactation phase, protein percentage, breed, or non-fat solids percentage. Farm, season, and protein percentage significantly influenced milk fermentation ability, renneting, and SCS. The lactose content is a good indicator of udder health. Full article

(This article belongs to the Special Issue Effect of Genetic and Nongenetic Factors on Functional and Milk Production Traits in Livestock)

Open AccessArticle

Identification of Genetic Polymorphisms of PI, PIII, and Exon 53 in the Acetyl-CoA Carboxylase-α (ACACα) Gene and Their Association with Milk Composition Traits of Najdi Sheep

Abdulkareem M. Matar

Abdulrahman S. Alharthi

Moez Ayadi

Maged A. Al-Garadi

and

Riyadh S. Aljummah

Animals 2023, 13(8), 1317; https://doi.org/10.3390/ani13081317 - 12 Apr 2023

Viewed by 1252

Abstract

Recently, increasing attention has been paid to sheep milk products, which are high in saturated fatty acids (SFA), and the extent of their impact on human health. This study aimed to identify SNPs for PI, PIII, and Exon 53 in the ACACα gene and their association with the MC and FA profiles in Najdi sheep milk. A total of 76 multiparous Najdi ewes were used, and they were maintained using the same feeding system. Milk and blood samples were collected during the first lactation. A genetic polymorphism analysis identified 20 SNPs: 4 SNPs on PI, 6 SNPs on PIII, and 10 SNPs on Exon 53. In PI, the SNP g.4412G > A was associated (p < 0.05) with palmitic acid (C16:0), palmitoleic acid (16:1 n-7) and linoleic acid (LA), while SNP g.4485C > G was associated with CLA and vaccenic acid (VA) (p < 0.05). Furthermore, in PIII, two SNPs (g.1168A > G and g.1331G > T) were associated with milk protein (p < 0.05), while the SNP g.6860G > C in Exon 53 was associated with milk fat (p < 0.05). SNPs in the Najdi breed have been shown to be strongly related to milk fat and EFA contents. This could support a genetic selection program and the control of milk traits in the Najdi breed of high-quality dairy sheep. Full article

(This article belongs to the Special Issue Effect of Genetic and Nongenetic Factors on Functional and Milk Production Traits in Livestock)

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Open AccessArticle

Non-Synonymous Variants in Fat QTL Genes among High- and Low-Milk-Yielding Indigenous Breeds

Neelam A. Topno

Veerbhan Kesarwani

Sandeep Kumar Kushwaha

and

Animals 2023, 13(5), 884; https://doi.org/10.3390/ani13050884 - 28 Feb 2023

Viewed by 1141

Abstract

The effect of breed on milk components—fat, protein, lactose, and water—has been observed to be significant. As fat is one of the major price-determining factors for milk, exploring the variations in fat QTLs across breeds would shed light on the variable fat content in their milk. Here, on whole-genome sequencing, 25 differentially expressed hub or bottleneck fat QTLs were explored for variations across indigenous breeds. Out of these, 20 genes were identified as having nonsynonymous substitutions. A fixed SNP pattern in high-milk-yielding breeds in comparison to low-milk-yielding breeds was identified in the genes GHR, TLR4, LPIN1, CACNA1C, ZBTB16, ITGA1, ANK1, and NTG5E and, vice versa, in the genes MFGE8, FGF2, TLR4, LPIN1, NUP98, PTK2, ZTB16, DDIT3, and NT5E. The identified SNPs were ratified by pyrosequencing to prove that key differences exist in fat QTLs between the high- and low-milk-yielding breeds. Full article

(This article belongs to the Special Issue Effect of Genetic and Nongenetic Factors on Functional and Milk Production Traits in Livestock)

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Figure 1

Open AccessArticle

Intra- and Interspecies RNA-Seq Based Variants in the Lactation Process of Ruminants

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Animals 2022, 12(24), 3592; https://doi.org/10.3390/ani12243592 - 19 Dec 2022

Viewed by 969

Abstract

The RNA-Seq data provides new opportunities for the detection of transcriptome variants’ single nucleotide polymorphisms (SNPs) in various species and tissues. Herein, milk samples from two sheep breeds and two cow breeds were utilized to characterize the genetic variation in the coding regions in three stages (before-peak (BP), peak (P), and after-peak (AP)) of the lactation process. In sheep breeds Assaf and Churra, 100,462 and 97,768, 65,996 and 62,161, and 78,656 and 39,245 variants were observed for BP, P, and AP lactation stages, respectively. The number of specific variants was 59,798 and 76,419, 11,483 and 49,210, and 104,033 and 320,817 in cow breeds Jersy and Kashmiri, respectively, for BP, P, and AP stages. Via the transcriptome analysis of variation in regions containing QTL for fat, protein percentages, and milk yield, we detected a number of pathways and genes harboring mutations that could influence milk production attributes. Many SNPs detected here can be regarded as appropriate markers for custom SNP arrays or genotyping platforms to conduct association analyses among commercial populations. The results of this study offer new insights into milk production genetic mechanisms in cow and sheep breeds, which can contribute to designing suitable breeding systems for optimal milk production. Full article

(This article belongs to the Special Issue Effect of Genetic and Nongenetic Factors on Functional and Milk Production Traits in Livestock)

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Figure 1

Open AccessArticle

Effects of Imported Semen Based on Different Selection Indices on Some Production and Reproduction Traits in Iranian Holstein Cattle

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Animals 2022, 12(21), 3054; https://doi.org/10.3390/ani12213054 - 07 Nov 2022

Viewed by 1008

Abstract

The aim of the present study was to evaluate the effects of imported semen of Holstein bulls from different countries on the economic traits of their daughters using the Lifetime Net Income (LNI) index in various climates of Iran. The data included the first lactation records of 274,057 Holstein cows collected during 1993 to 2017 by the Animal Breeding Center of Iran from 10 large dairy farms located in various provinces of Iran. The investigated traits included milk, fat and protein yields, calving age and calving interval. Breeding values of progenies were predicted by the Best Linear Unbiased Prediction (BLUP) method under the multi-trait animal model using DMU software. The genetic-economic merit of the progenies was estimated by the LNI index. There were significant differences between the estimated breeding values (EBVs) of sire groups (based on bull semen origin) for milk, fat and protein yields, calving age and calving interval in each climate (p < 0.01). The obtained results showed that the highest least-square means of LNI index in semi-cold, moderate and warm climates belonged to the daughters of French sires; however, daughters of German sires were estimated to have the highest least-square means in the cold climate. Full article

(This article belongs to the Special Issue Effect of Genetic and Nongenetic Factors on Functional and Milk Production Traits in Livestock)

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