scholarly journals Overview of Genomic Insights into Chicken Growth Traits Based on Genome- Wide Association Study and microRNA Regulation

2013 ◽  
Vol 14 (2) ◽  
pp. 137-146 ◽  
Author(s):  
Zhenqiang Xu ◽  
Qinghua Nie ◽  
Xiquan Zhang
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Genome Wide Association ◽  
Microrna Regulation ◽  
Genome Wide

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 Genome-wide association study reveals the genetic determinism of growth traits in a Gushi-Anka F2 chicken population

Heredity ◽  
2020 ◽  
Author(s):  
Yanhua Zhang ◽  
Yuzhe Wang ◽  
Yiyi Li ◽  
Junfeng Wu ◽  
Xinlei Wang ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Carcass Traits ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Pathway Enrichment Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Mechanisms

Abstract Chicken growth traits are economically important, but the relevant genetic mechanisms have not yet been elucidated. Herein, we performed a genome-wide association study to identify the variants associated with growth traits. In total, 860 chickens from a Gushi-Anka F2 resource population were phenotyped for 68 growth and carcass traits, and 768 samples were genotyped based on the genotyping-by-sequencing (GBS) method. Finally, 734 chickens and 321,314 SNPs remained after quality control and removal of the sex chromosomes, and these data were used to carry out a GWAS analysis. A total of 470 significant single-nucleotide polymorphisms (SNPs) for 43 of the 68 traits were detected and mapped on chromosomes (Chr) 1–6, -9, -10, -16, -18, -23, and -27. Of these, the significant SNPs in Chr1, -4, and -27 were found to be associated with more than 10 traits. Multiple traits shared significant SNPs, indicating that the same mutation in the region might have a large effect on multiple growth or carcass traits. Haplotype analysis revealed that SNPs within the candidate region of Chr1 presented a mosaic pattern. The significant SNPs and pathway enrichment analysis revealed that the MLNR, MED4, CAB39L, LDB2, and IGF2BP1 genes could be putative candidate genes for growth and carcass traits. The findings of this study improve our understanding of the genetic mechanisms regulating chicken growth and carcass traits and provide a theoretical basis for chicken breeding programs.

scholarly journals Genome-Wide Association Study Identified a Narrow Chromosome 1 Region Associated with Chicken Growth Traits

PLoS ONE ◽  
2012 ◽  
Vol 7 (2) ◽  
pp. e30910 ◽  
Author(s):  
Liang Xie ◽  
Chenglong Luo ◽  
Chengguang Zhang ◽  
Rong Zhang ◽  
Jun Tang ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Genome Wide Association ◽  
Chromosome 1 ◽  
Genome Wide

Genome‐wide association study of growth traits in Jinghai Yellow chicken hens using SLAF‐seq technology

2015 ◽  
Vol 50 (2) ◽  
pp. 175-176 ◽  
Author(s):  
W. H. Wang ◽  
J. Y. Wang ◽  
T. Zhang ◽  
Y. Wang ◽  
Y. Zhang ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Jinghai Yellow Chicken

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

Genes ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 189 ◽  
Author(s):  
Zhanwei Zhuang ◽  
Lingyang Xu ◽  
Jie Yang ◽  
Huijiang Gao ◽  
Lupei Zhang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Association Study ◽  
Muscle Development ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Average Daily Gain ◽  
Single Step ◽  
Genome Wide Association ◽  
Meat Production ◽  
Genome Wide

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.

scholarly journals Genome‑wide association study and genomic prediction for growth traits in yellow-plumage chicken using genotyping-by-sequencing

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Ruifei Yang ◽  
Zhenqiang Xu ◽  
Qi Wang ◽  
Di Zhu ◽  
Cheng Bian ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Prediction ◽  
Genetic Background ◽  
Prediction Accuracy ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Genome Wide Association ◽  
Genomic Feature ◽  
Genomic Information ◽  
Genome Wide

Abstract Background Growth traits are of great importance for poultry breeding and production and have been the topic of extensive investigation, with many quantitative trait loci (QTL) detected. However, due to their complex genetic background, few causative genes have been confirmed and the underlying molecular mechanisms remain unclear, thus limiting our understanding of QTL and their potential use for the genetic improvement of poultry. Therefore, deciphering the genetic architecture is a promising avenue for optimising genomic prediction strategies and exploiting genomic information for commercial breeding. The objectives of this study were to: (1) conduct a genome-wide association study to identify key genetic factors and explore the polygenicity of chicken growth traits; (2) investigate the efficiency of genomic prediction in broilers; and (3) evaluate genomic predictions that harness genomic features. Results We identified five significant QTL, including one on chromosome 4 with major effects and four on chromosomes 1, 2, 17, and 27 with minor effects, accounting for 14.5 to 34.1% and 0.2 to 2.6% of the genomic additive genetic variance, respectively, and 23.3 to 46.7% and 0.6 to 4.5% of the observed predictive accuracy of breeding values, respectively. Further analysis showed that the QTL with minor effects collectively had a considerable influence, reflecting the polygenicity of the genetic background. The accuracy of genomic best linear unbiased predictions (BLUP) was improved by 22.0 to 70.3% compared to that of the conventional pedigree-based BLUP model. The genomic feature BLUP model further improved the observed prediction accuracy by 13.8 to 15.2% compared to the genomic BLUP model. Conclusions A major QTL and four minor QTL were identified for growth traits; the remaining variance was due to QTL effects that were too small to be detected. The genomic BLUP and genomic feature BLUP models yielded considerably higher prediction accuracy compared to the pedigree-based BLUP model. This study revealed the polygenicity of growth traits in yellow-plumage chickens and demonstrated that the predictive ability can be greatly improved by using genomic information and related features.

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