Genome-wide associations and detection of potential candidate genes for direct genetic and maternal genetic effects influencing dairy cattle body weight at different ages

Yin, Tongming; König, Sven

doi:10.1186/s12711-018-0444-4

Cited by 33 publications

(30 citation statements)

References 52 publications

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“…Strong evidence of genomic signaling from chromosome 5 at the vicinity of base pair 106,987,567 was found by TPM at windows size of 2 [-log(P)=6.48e -10 ]. This finding is consistent with those of other studies that reported a weight gain gene CCND2 at the same genomic location [2,21,33]. Estimation of the proportion of genetic variance explained by detected SNPs found to be around 13% based on the Bayesian model.…”

Section: Discussionsupporting

confidence: 92%

“…To determine whether the various assumptions regarding genetic structure of the body weight gave different results, the number of mixtures were increased. BayesR [29] assumed a mixture of four normal distributions for predictions of SNP effects (assumed to be 0.00001, 0.0001, 0.001, and 0.01 genetic variances) in model (2). For each phenotype, the Markov Chain Monte Carlo (MCMC) algorithm was run for 1.000.000 samples, and the first 2000 samples were discarded as burn in period.…”

Section: Methodsmentioning

confidence: 99%

“…Body weight (BW) is an important heritable phenotype and related to other functional and productional traits in cattle [1]. Previous studies have reported positive genetic correlations between milk yield and BW [2]. [1] predicted longitudinal genetic correlations between BW and other functional traits, including dry matter intake and milking speed over days.…”

Section: Introductionmentioning

confidence: 99%

“…[1] predicted longitudinal genetic correlations between BW and other functional traits, including dry matter intake and milking speed over days. Heritability estimates of BW ranged from 0.32 to 0.61 [2,3] while estimates of BW change over the range from 0.10 to 0.34 [4,5]. Furthermore, BW plays critical role in fertility-and survival-related phenotypes [2].…”

Section: Introductionmentioning

confidence: 99%

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Across-breed genomic prediction for body weight in Siberian cattle populations

Karacaören¹

2020

Turk J Vet Anim Sci

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Body weight (BW) is an important heritable phenotype and related to other functional and production traits in cattle. The past decade has seen an increase in emphasis on genome wide association studies (GWAS) for detecting single nucleotide polymorphisms (SNPs) that are associated with quantitative phenotypes. Prediction of phenotypes using across-breed GWAS information [genomic prediction (GP)] is an also important research area but received less attention from the community. Understanding the link between major genes and common ancestors within and between breeds will contribute to a deeper understanding of GP across breeds. The aims of the present study were two-fold: 1) to examine genetic structure and to detect associated SNPs for BW using various single and multiple locus genomic models and 2) genomic prediction of BW using Siberian cattle populations based on across-breed genomic information. The most obvious finding to emerge from this study was the increase in the across-GP accuracy when gene segregation in both related populations was found. These findings have significant implications for the understanding of the way in which common ancestors and/or the presence of quantitative trait loci might affect the accuracy of the GP results.

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Section: Discussionsupporting

confidence: 92%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Across-breed genomic prediction for body weight in Siberian cattle populations

Karacaören¹

2020

Turk J Vet Anim Sci

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“…Many studies have reported QTLs and genes associated with growth traits in cattle (e.g., body weight and average daily gain) using the GWAS strategy [40,41]. However, few QTLs have consistently been identified as being associated with growth traits among breeds of cattle, including for Brangus heifers [42], Japanese Black (Wagyu) cattle [43], Charolais beef cattle [8], Siberia cattle [1], Nellore cattle [3], and the Chinese Simmental beef cattle examined in this study.…”

Section: Potential Genomic Regions and Candidate Genes Reveal The Commentioning

confidence: 85%

Weighted Single-Step Genome-Wide Association Study for Growth Traits in Chinese Simmental Beef Cattle

Zhuang

Yang

et al. 2020

Genes

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Improving the genetic process of growth traits is one of the major goals in the beef cattle industry, as it can increase meat production and reduce the cost of raising animals. Although several quantitative trait loci affecting growth traits in beef cattle have been identified, the genetic architecture of these economically important traits remains elusive. This study aims to map single nucleotide polymorphisms (SNPs) and genes associated with birth weight (BW), yearling weight (YW), average daily gain from birth to yearling (BYADG), and body weight at the age of 18 months (18MW) in a Chinese Simmental beef cattle population using a weighted, single-step, genome-wide association study (wssGWAS). Phenotypic and pedigree data from 6022 animals and genotypes from 744 animals (596,297 SNPs) were used for an association analysis. The results showed that 66 genomic windows explained 1.01-20.15% of the genetic variance for the four examined traits, together with the genes near the top SNP within each window. Furthermore, the identified genomic windows (>1%) explained 50.56%, 57.71%, 61.78%, and 37.82% of the genetic variances for BW, YW, BYADG, and 18MW, respectively. Genes with potential functions in muscle development and regulation of cell growth were highlighted as candidates for growth traits in Simmental cattle (SQOR and TBCB for BW, MYH10 for YW, RLF for BYADG, and ARHGAP31 for 18MW). Moreover, we found 40 SNPs that had not previously been identified as being associated with growth traits in cattle. These findings will further advance our understanding of the genetic basis for growth traits and will be useful for the molecular breeding of BW, YW, BYADG, and 18MW in the context of genomic selection in beef cattle.

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