Genome-Wide Association for Growth Traits in Canchim Beef Cattle

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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Extensive genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle

10.1101/2020.01.09.900902 ◽

2020 ◽

Cited By ~ 2

Author(s):

Camila U. Braz ◽

Troy N. Rowan ◽

Robert D. Schnabel ◽

Jared E. Decker

Keyword(s):

Climate Change ◽

Birth Weight ◽

Beef Cattle ◽

Functional Annotation ◽

Genetic Basis ◽

Growth Traits ◽

Genome Wide Association ◽

Phenotypic Variance ◽

Genotype By Environment ◽

Genome Wide

AbstractBackgroundUnderstanding the genetic basis of genotype-by-environment interactions (GxE) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. In addition, GxE information could also be useful to predict the vulnerability of populations to climate change.ResultsHere, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that GxE contribute 10%, 4%, and 3% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. GxE genome-wide association analysis (GWAA) detected a large number of GxE loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects between genotype classes regardless of differences in genotypic means. We also showed that variance-heterogeneity GWAA can detect loci enriched with GxE effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of GxE genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neural signaling, metabolic, hypoxia-induced, and immune system pathways. Knowledge of these pathways will be important as climate change becomes a burden on animal health and productivity. In addition, ecoregion-specific GxE SNPs detected in this study may play a crucial role in identifying resilient and adapted beef cattle across divergent environments.ConclusionsWe detected novel trait associations with large GxE effects for birth weight, weaning weight, and yearling weight. Functional annotation and pathway analysis uncovered genomic regions involved in response to environmental stimuli. We unraveled the relevance and complexity of the genetic basis of GxE underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals

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Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle

Scientific Reports ◽

10.1038/s41598-021-92455-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Camila U. Braz ◽

Troy N. Rowan ◽

Robert D. Schnabel ◽

Jared E. Decker

Keyword(s):

Beef Cattle ◽

Growth Traits ◽

Extensive Study ◽

Snp Markers ◽

Genome Wide Association ◽

Phenotypic Variance ◽

Genotype By Environment Interactions ◽

Association Analyses ◽

Genotype By Environment ◽

Genome Wide

AbstractUnderstanding genotype-by-environment interactions (G × E) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that G × E contribute 10.1%, 3.8%, and 2.8% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. G × E genome-wide association analysis (GWAA) detected a large number of G × E loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects regardless of differences in genotypic means. Further, variance-heterogeneity GWAA detected loci enriched with G × E effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of G × E genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neurotransmitter activity, hypoxia-induced processes, keratinization, hormone, thermogenic and immune pathways. We unraveled the relevance and complexity of the genetic basis of G × E underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals.

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PSXI-7 Genomic analysis of heterosis in a composite beef cattle breed

Journal of Animal Science ◽

10.1093/jas/skab235.445 ◽

2021 ◽

Vol 99 (Supplement_3) ◽

pp. 244-244

Author(s):

El Hamidi Hay ◽

Andrew Roberts

Keyword(s):

Birth Weight ◽

Beef Cattle ◽

Association Study ◽

Genome Wide Association Study ◽

Growth Traits ◽

Snp Markers ◽

Genome Wide Association ◽

Weaning Weight ◽

Genome Wide ◽

A Genome

Abstract Crossbreeding is widely used in the beef cattle industry to exploit benefits of heterosis. This study evaluated the effects of heterozygosity on growth traits in an Angus x Hereford cross population. Moreover, a genome wide association study was conducted to detect regions in the genome with significant dominance effects on growth traits contributing to heterosis. A total of 1,530 animals, comprised of pure Line 1 Hereford, Angus and Angus x Line 1 Hereford crosses, were evaluated. Phenotypes included birth weight, weaning weight and yearling weight. All animals were genotyped with GeneSeek GGP LD 50k. Effects of genomic heterozygosity on growth traits were estimated. These effects were -0.76 kg (P < 0.001), 4.67 kg (P < 0.0001), 42.39 kg (P < 0.02) on birth weight, weaning weight and yearling weight respectively. A genome wide association study revealed several SNP markers with significant heterotic effects associated with birth weight, weaning weight and yearling weight. These SNP markers were located on chromosomes 1, 2, 14, 19, 13 and 12. Genes in these regions were reported to be involved in growth and other important physiological mechanisms. Our study revealed several regions associated with dominance effects and contributing to heterosis. These results could be beneficial in optimizing crossbreeding.

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Genome-wide association study for feed efficiency and growth traits in U.S. beef cattle

BMC Genomics ◽

10.1186/s12864-017-3754-y ◽

2017 ◽

Vol 18 (1) ◽

Cited By ~ 54

Author(s):

Christopher M. Seabury ◽

David L. Oldeschulte ◽

Mahdi Saatchi ◽

Jonathan E. Beever ◽

Jared E. Decker ◽

...

Keyword(s):

Beef Cattle ◽

Association Study ◽

Feed Efficiency ◽

Genome Wide Association Study ◽

Growth Traits ◽

Genome Wide Association ◽

Genome Wide

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Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽

10.3390/ani11010192 ◽

2021 ◽

Vol 11 (1) ◽

pp. 192

Author(s):

Xinghai Duan ◽

Bingxing An ◽

Lili Du ◽

Tianpeng Chang ◽

Mang Liang ◽

...

Keyword(s):

Beef Cattle ◽

Candidate Genes ◽

Growth Curve ◽

Growth And Development ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Coefficient Of Determination ◽

Nucleotide Polymorphisms ◽

Genome Wide ◽

A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

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27. Genome wide association study for compensatory growth in Irish beef cattle

Animal - science proceedings ◽

10.1016/j.anscip.2021.03.028 ◽

2021 ◽

Vol 12 (1) ◽

pp. 17

Author(s):

Yvonne Mullins ◽

Alan Kelly ◽

David Kenny ◽

Sinead Waters

Keyword(s):

Beef Cattle ◽

Association Study ◽

Compensatory Growth ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Genome Wide

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Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

Genetics Selection Evolution ◽

10.1186/s12711-021-00649-8 ◽

2021 ◽

Vol 53 (1) ◽

Author(s):

Bingru Zhao ◽

Hanpeng Luo ◽

Xixia Huang ◽

Chen Wei ◽

Jiang Di ◽

...

Keyword(s):

Association Study ◽

Candidate Genes ◽

Genetic Improvement ◽

Genome Wide Association Study ◽

Growth Traits ◽

Fibre Diameter ◽

Single Step ◽

Genome Wide Association ◽

Six Traits ◽

Genome Wide

Abstract Background Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from − 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. Conclusions Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

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