scholarly journals Screening of Deletion Variants within the Goat PRDM6 Gene and Its Effects on Growth Traits

Animals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 208 ◽  
Author(s):  
Zhen Wang ◽  
Congliang Wang ◽  
Yongni Guo ◽  
Shuaishuai She ◽  
Baojing Wang ◽  
...  
Keyword(s):  
Growth Traits ◽  
Early Stage ◽  
Association Studies ◽  
Body Height ◽  
Shaanxi Province ◽  
Genome Wide Association Studies ◽  
Deletion Variant ◽  
Genome Wide ◽  
Hardy Weinberg Equilibrium ◽  
Pleiotropic Gene

By genome-wide association studies, the PRDM6 gene has been shown to affect multiple, apparently unrelated inherited traits, including bone density and body mass index. Therefore, it is considered a potentially pleiotropic gene. In this study, we identified a 12 bp deletion variant (NC_030814.1:rs651603667, g: 79985625-79985636delTTGACTGATCCA) within the PRDM6 gene in a large sample (SBWC goats; n = 1044). All goat samples were collected in Shaanxi province in July 2018. The frequency of the wt allele was higher than the frequency of the del allele, and this mutation polymorphism confirmed to be consistent with the Hardy–Weinberg equilibrium (p > 0.05). Further results showed that in a group of goats in the yearling period (18 months old, n = 567), this deletion variant of the PRDM6 gene was associated with heart girth (p = 0.027), cannon circumference (p = 0.008), chest depth (p = 2.10 × 10−5), chest width (p = 0.004), body height (p = 0.032), body length (p = 0.044) and hip-width (p = 0.014). For adult SBWC goats (36 months old, n = 477), the effects of the 12 bp variation on growth-related traits were found to make no difference. These findings show that the 12 bp deletion within the goat PRDM6 gene plays an important role in the early growth and development of goats. Using the 12 bp mutation, breeders can quickly and effectively select excellent individual goats at an early stage.

scholarly journals Genome-wide association studies for feedlot and growth traits in cattle1

2011 ◽  
Vol 89 (6) ◽  
pp. 1684-1697 ◽  
Author(s):  
S. Bolormaa ◽  
B. J. Hayes ◽  
K. Savin ◽  
R. Hawken ◽  
W. Barendse ◽  
...  
Keyword(s):  
Growth Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Unravelling the complex genetic basis of growth in New Zealand silver trevally (Pseudocaranx georgianus)

2021 ◽  
Author(s):  
Noemie Valenza-Troubat ◽  
Sara Montanari ◽  
Peter Ritchie ◽  
Maren Wellenreuther
Keyword(s):  
Qtl Mapping ◽  
Complex Traits ◽  
Genetic Basis ◽  
Growth Traits ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Powerful Approach ◽  
Trait Locus

AbstractGrowth directly influences production rate and therefore is one of the most important and well-studied trait in animal breeding. However, understanding the genetic basis of growth has been hindered by its typically complex polygenic architecture. Here, we performed quantitative trait locus (QTL) mapping and genome-wide association studies (GWAS) for 10 growth traits that were observed over two years in 1,100 F1 captive-bred trevally (Pseudocaranx georgianus). We constructed the first high-density linkage map for trevally, which included 19,861 single nucleotide polymorphism (SNP) markers, and discovered eight QTLs for height, length and weight on linkage groups 3, 14 and 18. Using GWAS, we further identified 113 SNP-trait associations, uncovering 10 genetic hot spots involved in growth. Two of the markers found in the GWAS co-located with the QTLs previously mentioned, demonstrating that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex traits. This is the first study of its kind for trevally. Our findings provide important insights into the genetic architecture of growth in this species and supply a basis for fine mapping QTLs, marker-assisted selection, and further detailed functional analysis of the genes underlying growth in trevally.

Transcriptome-wide association study identifies genetically dysregulated genes in diabetic neuropathy

2020 ◽  
Vol 23 ◽  
Author(s):  
Danfeng Lan ◽  
Hong-Yan Jiang ◽  
Xiaoyang Su ◽  
Yan Zhao ◽  
Sicheng Du ◽  
...  
Keyword(s):  
Sciatic Nerve ◽  
Diabetic Neuropathy ◽  
Mouse Models ◽  
Disease Burden ◽  
Large Scale ◽  
Early Stage ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Fusion Algorithm ◽  
Genome Wide

Background: Complications are the main cause of the disease burden of diabetes. Genes determining the development and progression of complications remain to be identified. Diabetic neuropathy is the most common and debilitating complication and mainly affects the nerves of legs and feet. In this study, we attempted to identify diabetic neuropathy-specific genes from reliable large-scale genome-wide association studies (GWASs) for diabetes per se. Methods: Taking advantage of publicly available data, we initially converted the GWAS signals to transcriptomic profiles in the tibial nerve using the functional summary-based imputation (FUSION) algorithm. The FUSION-derived genes were then checked to determine whether they were differentially expressed in the sciatic nerve of mouse models of diabetic neuropathy. The dysregulated genes identified in the sciatic nerve were explored in the blood of patients. Results: We found that eleven genes out of 452 FUSION-derived genes were regulated by diabetes GWAS loci and were altered in the sciatic nerve of mouse models with early-stage neuropathy. Among the eleven genes, significant (Pvalue<0.05) expression alterations of HSD17B4, DHX32, MERTK, and SFXN4 could be detected in the blood of human patients. Conclusions: Our analyses identified genes with an effect in the sciatic nerve and provided the possibility of noninvasive early detection of diabetic neuropathy.

scholarly journals Haplotype-based genome-wide association studies for carcass and growth traits in chicken

2020 ◽  
Vol 99 (5) ◽  
pp. 2349-2361 ◽  
Author(s):  
Hui Zhang ◽  
Lin-Yong Shen ◽  
Zi-Chun Xu ◽  
Luke M. Kramer ◽  
Jia-Qiang Yu ◽  
...  
Keyword(s):  
Growth Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies for growth traits in buffaloes using the single step genomic BLUP

2019 ◽  
Vol 61 (1) ◽  
pp. 113-115 ◽  
Author(s):  
Francisco Ribeiro de Araujo Neto ◽  
Daniel Jordan de Abreu Santos ◽  
Gerardo Alves Fernandes Júnior ◽  
Rusbel Raul Aspilcueta-Borquis ◽  
André Vieira do Nascimento ◽  
...  
Keyword(s):  
Growth Traits ◽  
Association Studies ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

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 Estimation of complex effect-size distributions using summary-level statistics from genome-wide association studies across 32 complex traits and implications for the future

2017 ◽  
Author(s):  
Yan Zhang ◽  
Guanghao Qi ◽  
Ju-Hyun Park ◽  
Nilanjan Chatterjee
Keyword(s):  
Effect Size ◽  
Complex Traits ◽  
Growth Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Size Distributions ◽  
Normal Mixture ◽  
Genome Wide ◽  
Level Statistics

AbstractSummary-level statistics from genome-wide association studies are now widely used to estimate heritability and co-heritability of traits using the popular linkage-disequilibrium-score (LD-score) regression method. We develop a likelihood-based approach for analyzing summary-level statistics and external LD information to estimate common variants effect-size distributions, characterized by proportion of underlying susceptibility SNPs and a flexible normal-mixture model for their effects. Analysis of summary-level results across 32 GWAS reveals that while all traits are highly polygenic, there is wide diversity in the degrees of polygenicity. The effect-size distributions for susceptibility SNPs could be adequately modeled by a single normal distribution for traits related to mental health and ability and by a mixture of two normal distributions for all other traits. Among quantitative traits, we predict the sample sizes needed to identify SNPs which explain 80% of GWAS heritability to be between 300K-500K for some of the early growth traits, between 1-2 million for some anthropometric and cholesterol traits and multiple millions for body mass index and some others. The corresponding predictions for disease traits are between 200K-400K for inflammatory bowel diseases, close to one million for a variety of adult onset chronic diseases and between 1-2 million for psychiatric diseases.

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