Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Background The body conformation traits of dairy cattle are closely related to their production performance and health. The present study aimed to identify gene variants associated with body conformation traits in Chinese Holstein cattle and provide marker loci for genomic selection in dairy cattle breeding. These findings could offer robust theoretical support for optimizing the health of dairy cattle and enhancing their production performance. ResultsThis study involved 586 Chinese Holstein cattle and used the predicted transmitting abilities (PTAs) of 17 body conformation traits evaluated by the Council on Dairy Cattle Breeding in the USA as phenotypic values. These traits were categorized into body size traits, rump traits, feet/legs traits, udder traits, and dairy characteristic traits. On the basis of the genomic profiling results from the Genomic Profiler Bovine 100 K SNP chip, genotype data were quality controlled via PLINK software, and 586 individuals and 80,713 SNPs were retained for further analysis. Genomewide association studies (GWASs) were conducted via GEMMA software, which employs both univariate linear mixed models (LMMs) and multivariate linear mixed models (mvLMMs). The Bonferroni method was used to determine the significance threshold, identifying gene variants significantly associated with body conformation traits in Chinese Holstein cattle. The single-trait GWAS identified 24 SNPs significantly associated with body conformation traits (P < 0.01), with annotation leading to the identification of 21 candidate genes. The multi-trait GWAS identified 54 SNPs, which were annotated to 57 candidate genes, including 39 new SNPs not identified in the single-trait GWAS. Additionally, 14 SNPs in the 86.84-87.41 Mb region of chromosome 6 were significantly associated with multiple traits, such as body size, udder, and dairy characteristics. Four genes-SLC4A4, GC, NPFFR2, and ADAMTS3-were annotated in this region.Conclusions A total of 63 SNPs were identified as significantly associated with 17 body conformation traits in Chinese Holstein cattle through both single-trait and multi-trait GWAS analyses. Sixty-six candidate genes were annotated, with 12 genes identified by both methods, such as SLC4A4, GC, NPFFR2, and ADAMTS3, which are involved in pathways such as growth hormone synthesis and secretion, sphingolipid signaling, and dopaminergic synapse pathways. These findings provide potential genetic marker information related to body conformation traits for the breeding of Chinese Holstein cattle.
Background The body conformation traits of dairy cattle are closely related to their production performance and health. The present study aimed to identify gene variants associated with body conformation traits in Chinese Holstein cattle and provide marker loci for genomic selection in dairy cattle breeding. These findings could offer robust theoretical support for optimizing the health of dairy cattle and enhancing their production performance. ResultsThis study involved 586 Chinese Holstein cattle and used the predicted transmitting abilities (PTAs) of 17 body conformation traits evaluated by the Council on Dairy Cattle Breeding in the USA as phenotypic values. These traits were categorized into body size traits, rump traits, feet/legs traits, udder traits, and dairy characteristic traits. On the basis of the genomic profiling results from the Genomic Profiler Bovine 100 K SNP chip, genotype data were quality controlled via PLINK software, and 586 individuals and 80,713 SNPs were retained for further analysis. Genomewide association studies (GWASs) were conducted via GEMMA software, which employs both univariate linear mixed models (LMMs) and multivariate linear mixed models (mvLMMs). The Bonferroni method was used to determine the significance threshold, identifying gene variants significantly associated with body conformation traits in Chinese Holstein cattle. The single-trait GWAS identified 24 SNPs significantly associated with body conformation traits (P < 0.01), with annotation leading to the identification of 21 candidate genes. The multi-trait GWAS identified 54 SNPs, which were annotated to 57 candidate genes, including 39 new SNPs not identified in the single-trait GWAS. Additionally, 14 SNPs in the 86.84-87.41 Mb region of chromosome 6 were significantly associated with multiple traits, such as body size, udder, and dairy characteristics. Four genes-SLC4A4, GC, NPFFR2, and ADAMTS3-were annotated in this region.Conclusions A total of 63 SNPs were identified as significantly associated with 17 body conformation traits in Chinese Holstein cattle through both single-trait and multi-trait GWAS analyses. Sixty-six candidate genes were annotated, with 12 genes identified by both methods, such as SLC4A4, GC, NPFFR2, and ADAMTS3, which are involved in pathways such as growth hormone synthesis and secretion, sphingolipid signaling, and dopaminergic synapse pathways. These findings provide potential genetic marker information related to body conformation traits for the breeding of Chinese Holstein cattle.
Background The body conformation traits of dairy cattle are closely related to their production performance and health. The present study aimed to identify gene variants associated with body conformation traits in Chinese Holstein cattle and provide marker loci for genomic selection in dairy cattle breeding. The study findings could offer robust theoretical support to optimize the health of dairy cattle and enhance their production performance. Results This study involved 586 Chinese Holstein cows, using the predicted transmitting abilities (PTAs) of 17 body conformation traits evaluated by the Council on Dairy Cattle Breeding in the USA as phenotypic values. These traits were categorized into body size traits, rump traits, feet/legs traits, udder traits, and dairy characteristic traits. Based on the genomic profiling results from the Genomic Profiler Bovine 100K SNP chip, genotype data were quality-controlled using PLINK software, retaining 586 individuals and 80,713 SNPs for further analysis. Genome-wide association studies (GWAS) were conducted using the GEMMA software, employing both univariate linear mixed models (LMM) and multivariate linear mixed models (mvLMM). The Bonferroni method was used to determine the significance threshold, identifying gene variants significantly associated with body conformation traits in Chinese Holstein cows. The single-trait GWAS identified 24 SNPs significantly associated with body conformation traits (P < 0.01), with annotation leading to the identification of 21 candidate genes. The multivariate GWAS identified 54 SNPs, which were annotated to 57 candidate genes, including 39 new SNPs not identified in the single-trait GWAS. Additionally, 14 SNPs in the 86.84–87.41 Mb region of chromosome 6 were significantly associated with multiple traits such as body size, udder, and dairy characteristics. Four genes—SLC4A4, GC, NPFFR2, and ADAMTS3—were annotated in this region. Conclusions A total of 63 SNPs were identified as significantly associated with the 17 body conformation traits in Chinese Holstein cows through both single-trait and multivariate GWAS analyses. Sixty-six candidate genes were annotated, with 12 genes identified by both methods, including SLC4A4, GC, NPFFR2, and ADAMTS3, which are involved in biological processes such as active glucose transport, adipogenesis, and neural development. Thus, the study findings provided potential genetic marker information related to body conformation traits for the breeding of Chinese Holstein cattle.
The article presents the results of a search for genome-wide associations with phenotypic traits characterizing the growth and development of sheep from a crossbred population obtained from crossing Romanov sheep and F1 hybrid rams (Romanov sheep x Katahdin). The phenotype database included ten body measurements (withers height, sacral height, back height, chest depth, chest width, ischial tuberosity width, body length, oblique body length, chest girth, pastern girth) recorded at the age of 6 days, 3, 6 and 9 months. Genotyping of sheep was carried out using high-density DNA chips containing about 600,000 SNP markers. Genome-wide association studies (GWAS) were performed using regression analysis in the STATISTICA 10 program. The search for candidate genes localized in the SNP region was performed using Ensembl genome browser 110. There was carried out an analysis of the matches of the identified SNPs with known quantitative trait loci (QTLs) described in the Sheep Quantitative Trait Locus Database. There were found SNPs that were significantly associated with the studied phenotypic traits overlapped with the QTLs, among which the most common categories were “Body weight (slaughter)”, “Muscle weight in carcass”, “Body weight (live)” and “Bone weight in carcass”. There has been established that SNPs significantly associated with exterior traits were localized within or in the immediate vicinity of 64 genes. There were found potential candidates regulating the growth of muscle (FOXO3, PRKAG3, MYOZ2, and ANKRD1) and cartilage tissues FGF12) and involved in metabolic processes, which were critical for the growth of lambs (CLDN, ALB, and MRC1). Along with the known in sheep functional candidates (CAST and SCD5) , there were identified genes that were not previously described in sheep, but regulated growth and development processes in other livestock species including genes RAB28, PRKAG3 and FOXO3. The identified SNPs can be recommended for inclusion in marker-guided selection programs in sheep breeding.
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.