scholarly journals Genome-wide association analyses of plant growth traits during the stem elongation phase in wheat

2018 ◽  
Vol 16 (12) ◽  
pp. 2042-2052 ◽  
Author(s):  
Zifeng Guo ◽  
Guozheng Liu ◽  
Marion S. Röder ◽  
Jochen C. Reif ◽  
Martin W. Ganal ◽  
...  
Keyword(s):  
Plant Growth ◽  
Growth Traits ◽  
Stem Elongation ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Genome Wide ◽  
Elongation Phase

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.

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 250 Genome wide Association analyses for meat quality traits in multibreed and crossbred beef cattle.

2018 ◽  
Vol 96 (suppl_3) ◽  
pp. 84-84
Author(s):  
M Abo-Ismail ◽  
J Crowley ◽  
E Akanno ◽  
C Li ◽  
P Stothard ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Meat Quality ◽  
Genome Wide Association ◽  
Quality Traits ◽  
Association Analyses ◽  
Meat Quality Traits ◽  
Genome Wide

scholarly journals Genome-wide association analyses in east Asians identify new susceptibility loci for colorectal cancer

2012 ◽  
Vol 45 (2) ◽  
pp. 191-196 ◽  
Author(s):  
Wei-Hua Jia ◽  
◽  
Ben Zhang ◽  
Keitaro Matsuo ◽  
Aesun Shin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Genome Wide Association ◽  
Susceptibility Loci ◽  
East Asians ◽  
Association Analyses ◽  
Genome Wide

scholarly journals Candidate Variants for Additive and Interactive Effects on Bioenergy Traits in Switchgrass ( Panicum virgatum L.) Identified by Genome‐Wide Association Analyses

2018 ◽  
Vol 11 (3) ◽  
pp. 180002 ◽  
Author(s):  
Guillaume P. Ramstein ◽  
Joseph Evans ◽  
Aruna Nandety ◽  
Malay C. Saha ◽  
E. Charles Brummer ◽  
...  
Keyword(s):  
Panicum Virgatum ◽  
Interactive Effects ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Genome Wide ◽  
Panicum Virgatum L
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