Identification of genetic markers that affect economically important traits is of high value from a biological point of view, enabling the targeting of candidate genes and providing practical benefits for the industry such as wide-scale genomic selection. This study is one of the first to investigate the genetic background of economically important traits in dairy goats using the caprine 50K single nucleotide polymorphism (SNP) chip. The aim of the project was to perform a genome-wide association study for milk yield and conformation of udder, teat, and feet and legs. A total of 137,235 milk yield records on 4,563 goats each scored for 10 conformation traits were available. Out of these, 2,381 goats were genotyped with the Illumina Caprine 50K BeadChip (Illumina Inc., San Diego, CA). A range of pseudo-phenotypes were used including deregressed breeding values and pseudo-estimated breeding values. Genome-wide association studies were performed using the multi-locus mixed model (MLMM) algorithm implemented in SNP & Variation Suite v7.7.8 (Golden Helix Inc., Bozeman, MT). A genome-wise significant [-log(P-value) > 5.95] SNP for milk yield was identified on chromosome 19, with additional chromosome-wise significant (-log(P-value) > 4.46] SNP on chromosomes 4, 8, 14, and 29. Three genome-wise significant SNP for conformation of udder attachment, udder depth, and front legs were identified on chromosome 19, and chromosome-wise SNP were found on chromosomes 4, 5, 6, 10, 11, 12, 13, 14, 15, 16, 17, 18, 21, 23, and 27. The proportion of variance explained by the significant SNP was between 0.4 and 7.0% for milk yield and between 0.1 and 13.8% for conformation traits. This study is the first attempt to identify SNP associated with milk yield and conformation in dairy goats. Two genome-wise significant SNP for milk yield and 3 SNP for conformation of udder attachment, udder depth, and front legs were found. Our results suggest that conformation traits have a polygenic background because, for most of them, we did not identify any quantitative trait loci with major effect.
Sheep are considered as a major contributor of global food security. Moreover, sheep preweaning growth traits as well as in vivo carcass composition traits such as ultrasonic measurements of Longissimus dorsi muscle depth (UMD) and back‐fat thickness (UFD) are crucially important indicators of meat yield and hot carcass composition. Despite their relative importance for productivity and profitability of a sheep production system, detected QTL for these traits are quite scarce. Therefore, we implemented GWAS for these traits using animal mixed model‐based association approach provided by GenABEL in Esme sheep. Three genome‐wide and 14 individual chromosome‐wide associated SNPs were discovered. As a result, ESRP1, LOC105613082, ZNF641, DUSP5, TEAD1, SMOX, PTPRT, RALYL, POM121C, PHIP, LOC101106051, ZIM3, PEG3, TRPC7, FBXL4, LOC105610397, LOC105616489 and DNAAF2 were suggested as candidates. Some of the discovered genes and involved pathways were already annotated to contribute growth and development in various species including human, mice and cattle. All in all, the results of this study are expected to strongly contribute to shed a light on the underlying molecular mechanisms behind growth and carcass composition traits, with potential implications on studies aiming faster genetic improvement, targeted low‐resolution SNP panel designs and genome‐editing studies.
In the current study, the genetic architecture of growth and linear type traits were investigated in Akkaraman sheep. Estimations of genomic heritability, genetic correlations, and phenotypic correlations were implemented for 17 growth and linear type traits of 473 Akkaraman lambs by the univariate and multivariate analysis of animal mixed models. Correspondingly, moderate heritability estimates, as well as high and positive genetic/phenotypic correlations were found between growth and type traits. On the other hand, 2 genome-wide and 19 chromosome-wide significant single nucleotide polymorphisms were found to be associated with the traits as a result of animal mixed model-based genome-wide association analyses. Accordingly, we propose several genes located on different chromosomes (e.g., PRDM2, PTGDR, PTPRG, KCND2, ZNF260, CPE, GRID2, SCD5, SPIDR, ZNF407, HCN3, TMEM50A, FKBP1A, TLE4, SP1, SLC44A1, and MYOM3) as putative quantitative trait loci for the 22 growth and linear type traits studied. In our study, specific genes (e.g., TLE4, PTGDR, and SCD5) were found common between the traits studied, suggesting an interplay between the genetic backgrounds of these traits. The fact that four of the proposed genes (TLE4, MYOM3, SLC44A1, and TMEM50A) are located on sheep chromosome 2 confirms the importance of these genomic regions for growth and morphological structure in sheep. The results of our study are therefore of great importance for the development of efficient selection indices and marker-assisted selection programs, as well as for the understanding of the genetic architecture of growth and linear traits in sheep.
Use of genomic information in ruminant production systems can help relieve concerns related to food security and sustainability of production. Nutritional genomics (i.e., Nutrigenomics) is a field of research that is interested in all types of reciprocal interactions between nutrients and genomes of organisms, i.e., variable patterns of gene expression and effect of genetic variations on the nutritional environment. Devising a revolutionizing analytical approach to traditional ruminant nutrition research, the relatively novel area of ruminant nutrigenomics has several studies concerning different aspects of animal production systems. This paper aims to review the current nutrigenomics research in the frame of how nutrition of ruminants can be modified accounting for individual genetic backgrounds and gene/diet relationships behind productivity, quality, efficiency, disease resistance, fertility, and GHG emissions. Furthermore, current challenges facing ruminant nutrigenomics are evaluated and future directions for the novel area are strongly argued by this review.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.