scholarly journals Genome-wide association and genotype by environment interactions for growth traits in U.S. Gelbvieh cattle

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Johanna L. Smith ◽  
Miranda L. Wilson ◽  
Sara M. Nilson ◽  
Troy N. Rowan ◽  
David L. Oldeschulte ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Feed Efficiency ◽  
Growth Traits ◽  
Genome Wide Association ◽  
Positional Candidate ◽  
Genotype By Environment ◽  
Genome Wide ◽  
Nominal Significance ◽  
Pleiotropic Qtl ◽  
Heritability Estimates

Abstract Background Single nucleotide polymorphism (SNP) arrays have facilitated discovery of genetic markers associated with complex traits in domestic cattle; thereby enabling modern breeding and selection programs. Genome-wide association analyses (GWAA) for growth traits were conducted on 10,837 geographically diverse U.S. Gelbvieh cattle using a union set of 856,527 imputed SNPs. Birth weight (BW), weaning weight (WW), and yearling weight (YW) were analyzed using GEMMA and EMMAX (via imputed genotypes). Genotype-by-environment (GxE) interactions were also investigated. Results GEMMA and EMMAX produced moderate marker-based heritability estimates that were similar for BW (0.36–0.37, SE = 0.02–0.06), WW (0.27–0.29, SE = 0.01), and YW (0.39–0.41, SE = 0.01–0.02). GWAA using 856K imputed SNPs (GEMMA; EMMAX) revealed common positional candidate genes underlying pleiotropic QTL for Gelbvieh growth traits on BTA6, BTA7, BTA14, and BTA20. The estimated proportion of phenotypic variance explained (PVE) by the lead SNP defining these QTL (EMMAX) was larger and most similar for BW and YW, and smaller for WW. Collectively, GWAAs (GEMMA; EMMAX) produced a highly concordant set of BW, WW, and YW QTL that met a nominal significance level (P ≤ 1e-05), with prioritization of common positional candidate genes; including genes previously associated with stature, feed efficiency, and growth traits (i.e., PLAG1, NCAPG, LCORL, ARRDC3, STC2). Genotype-by-environment QTL were not consistent among traits at the nominal significance threshold (P ≤ 1e-05); although some shared QTL were apparent at less stringent significance thresholds (i.e., P ≤ 2e-05). Conclusions Pleiotropic QTL for growth traits were detected on BTA6, BTA7, BTA14, and BTA20 for U.S. Gelbvieh beef cattle. Seven QTL detected for Gelbvieh growth traits were also recently detected for feed efficiency and growth traits in U.S. Angus, SimAngus, and Hereford cattle. Marker-based heritability estimates and the detection of pleiotropic QTL segregating in multiple breeds support the implementation of multiple-breed genomic selection.

scholarly journals 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

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.

scholarly journals Single-step genome-wide association study for social genetic effects and direct genetic effects on growth in Landrace pigs

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Joon-Ki Hong ◽  
Jae-Bong Lee ◽  
Yuliaxis Ramayo-Caldas ◽  
Si-Dong Kim ◽  
Eun-Seok Cho ◽  
...  
Keyword(s):  
Animal Model ◽  
Association Study ◽  
Candidate Genes ◽  
Genome Wide Association Study ◽  
Single Step ◽  
Genetic Effects ◽  
Genome Wide Association ◽  
Positional Candidate ◽  
Network Analyses ◽  
Genome Wide

Abstract In livestock social interactions, social genetic effects (SGE) represent associations between phenotype of one individual and genotype of another. Such associations occur when the trait of interest is affected by transmissible phenotypes of social partners. The aim of this study was to estimate SGE and direct genetic effects (DGE, genetic effects of an individual on its own phenotype) on average daily gain (ADG) in Landrace pigs, and to conduct single-step genome-wide association study using SGE and DGE as dependent variables to identify quantitative trait loci (QTLs) and their positional candidate genes. A total of 1,041 Landrace pigs were genotyped using the Porcine SNP 60K BeadChip. Estimates of the two effects were obtained using an extended animal model. The SGE contributed 16% of the total heritable variation of ADG. The total heritability estimated by the extended animal model including both SGE and DGE was 0.52. The single-step genome-wide association study identified a total of 23 QTL windows for the SGE on ADG distributed across three chromosomes (i.e., SSC1, SSC2, and SSC6). Positional candidate genes within these QTL regions included PRDM13, MAP3K7, CNR1, HTR1E, IL4, IL5, IL13, KIF3A, EFHD2, SLC38A7, mTOR, CNOT1, PLCB2, GABRR1, and GABRR2, which have biological roles in neuropsychiatric processes. The results of biological pathway and gene network analyses also support the association of the neuropsychiatric processes with SGE on ADG in pigs. Additionally, a total of 11 QTL windows for DGE on ADG in SSC2, 3, 6, 9, 10, 12, 14, 16, and 17 were detected with positional candidate genes such as ARL15. We found a putative pleotropic QTL for both SGE and DGE on ADG on SSC6. Our results in this study provide important insights that can help facilitate a better understanding of the molecular basis of SGE for socially affected traits.

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

2020 ◽  
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

scholarly journals Genome-wide Association Study for Noise-induced Cochlear Synaptopathy

2018 ◽  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Noise Exposure ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Positional Candidate ◽  
Genome Wide ◽  
Hybrid Mouse Diversity Panel ◽  
Susceptibility To Noise ◽  
Cell Synapse

Article SummaryIn order to elucidate the genetic architecture of the auditory hair cell synapse and the susceptibility to noise-induced cochlear synaptopathy, we are providing the first genome-wide association study with 111 strains (n=695) of the Hybrid Mouse Diversity Panel based upon the strain variation of the wave 1 P1-N1 amplitude of the auditory brainstem responses both before and after noise exposure. Based on this association analysis and our cochlear gene expression data, we identified several novel loci and prioritized positional candidate genes related to cochlear synaptopathy, especially after exposure to noise.AbstractThis is the first genome-wide association study (GWAS) with the Hybrid Mouse Diversity Panel (HMDP) to define the genetic landscape of the auditory hair cell synapse and the susceptibility to noise-induced cochlear synaptopathy. We tested 5-week old female mice (n=695) from 111 HMDP strains (n= 6-7/strain) at baseline and post noise exposure using ABR wave 1 suprathreshold amplitudes (P1-N1 at 80 dB SPL) at 8, 12, 16, 24 and 32 kHz tone burst stimuli. Mice were exposed for 2 hours to 10 kHz octave band noise (OBN) at 108 dB SPL. A broad range of suprathreshold ABR wave 1 amplitude were detected across the HMDP strains. At the genome-wide significance threshold (-logP = 5.39), associations on Chr. 3 and Chr. 16 were identified at baseline. Also, association peaks on Chr. 2 and Chr. 13 were determined post noise exposure. In order to prioritize candidate genes, we generated gene expression microarray profiles using RNA isolated from cochleae in 64 HMDP strains (n =3 arrays per strain). We then used EMMA to perform an association analysis between all SNPs and array probes mapping within each region. A total of 17 genes (2 within Chr. 3 association, 6 within Chr. 2 association and 9 within Chr. 13 association) of these 3 loci were identified with at least 1 probe whose expression was regulated by a significant cis eQTL in the cochlea. Also, the genetic architecture of noise induced cochlear synaptopathy is distinct from that of baseline auditory nerve/synapse integrity. In summary, from this GWAS and our eQTL data, we identified 4 novel loci and prioritized positional candidate genes related to cochlear synaptopathy at baseline and after exposure to noise.

scholarly journals Genome-wide association studies for growth traits in broilers

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Dachang Dou ◽  
Linyong Shen ◽  
Jiamei Zhou ◽  
Zhiping Cao ◽  
Peng Luan ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Candidate Genes ◽  
Rapid Growth ◽  
Genetic Parameters ◽  
Growth Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Methods ◽  
Genome Wide

Abstract Background The identification of markers and genes for growth traits may not only benefit for marker assist selection /genomic selection but also provide important information for understanding the genetic foundation of growth traits in broilers. Results In the current study, we estimated the genetic parameters of eight growth traits in broilers and carried out the genome-wide association studies for these growth traits. A total of 113 QTNs discovered by multiple methods together, and some genes, including ACTA1, IGF2BP1, TAPT1, LDB2, PRKCA, TGFBR2, GLI3, SLC16A7, INHBA, BAMBI, APCDD1, GPR39, and GATA4, were identified as important candidate genes for rapid growth in broilers. Conclusions The results of this study will provide important information for understanding the genetic foundation of growth traits in broilers.

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

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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