scholarly journals A single-step genome wide association study on Body Size Traits using imputation-based whole-genome sequence data in Yorkshire pigs

2020 ◽  
Author(s):  
Huatao Liu ◽  
Hailiang Song ◽  
Yifan Jiang ◽  
Yao Jiang ◽  
Fengxia Zhang ◽  
...  
Keyword(s):  
Body Size ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Single Step ◽  
The Body ◽  
Genome Wide Association ◽  
Sequencing Data ◽  
Genome Wide ◽  
Yorkshire Pigs ◽  
Trait Model

Abstract Background: The body shape of pig is the most direct production index of pig, which can fully reflect the growth status of pig and is closely related to some important economic traits. In this study, genome-wide association study on seven body size traits, the body length (BL), height (BH), chest circumference (CC), abdominal circumference (AC), cannon bone circumference (CBC), rump width (RW) and chest width (CW) were conducted in Yorkshire pigs. Methods: Illumina Porcine 80K SNP chip were used to genotype 589 of 5,572 Yorkshire pigs with body size records, and then the chip data was imputed to sequencing data. After quality control of imputed sequencing data, 784,267 SNPs were obtained, and the averaged linkage disequilibrium (r2) was 0.191. We used the single-trait model and the two-trait model to conduct single-step genome wide association study (ssGWAS) on seven body size traits.Results: A total of 198 significant SNPS were finally identified according to the P value and the contribution to the genetic variance of individual SNP. 11 candidate genes (CDH13, SIL2, CDC14A, TMRPSS15, TRAPPC9, CTNND2, KDM6B, CHD3, MUC13, MAPK4 and HMGA1) were found to be associated with body size traits in pigs, KDM6B and CHD3 jointly affect AC and CC, and MUC13 jointly affect RW and CW. These genes are involved in the regulation of bone growth and development as well as the absorption of nutrients and are associated with obesity. HMGA1 is proposed as strong candidate gene for body size traits because of its important function and high consistency with other studies regarding the regulation of body size traits. Our results could provide valuable information for pig breeding based on molecular breeding.

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 novel loci associated with body size and carcass yields in Pekin ducks

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Meng-Ting Deng ◽  
Feng Zhu ◽  
Yu-Ze Yang ◽  
Fang-Xi Yang ◽  
Jin-ping Hao ◽  
...  
Keyword(s):  
Body Size ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Pekin Ducks ◽  
Genome Wide

scholarly journals A Genome-Wide Association Study for Clinical Mastitis in First Parity US Holstein Cows Using Single-Step Approach and Genomic Matrix Re-Weighting Procedure

PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0114919 ◽  
Author(s):  
Francesco Tiezzi ◽  
Kristen L. Parker-Gaddis ◽  
John B. Cole ◽  
John S. Clay ◽  
Christian Maltecca
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Clinical Mastitis ◽  
Single Step ◽  
Genome Wide Association ◽  
Holstein Cows ◽  
Genome Wide ◽  
A Genome

scholarly journals Genome-Wide Association Study Based on Multiple Imputation with Low-Depth Sequencing Data: Application to Biofuel Traits in Reed Canarygrass

2015 ◽  
Vol 5 (5) ◽  
pp. 891-909 ◽  
Author(s):  
Guillaume P. Ramstein ◽  
Alexander E. Lipka ◽  
Fei Lu ◽  
Denise E. Costich ◽  
Jerome H. Cherney ◽  
...  
Keyword(s):  
Association Study ◽  
Multiple Imputation ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Sequencing Data ◽  
Reed Canarygrass ◽  
Genome Wide ◽  
Data Application

scholarly journals Single-Step Genome-Wide Association Study for Resistance to Piscirickettsia salmonis in Rainbow Trout (Oncorhynchus mykiss)

2019 ◽  
Vol 9 (11) ◽  
pp. 3833-3841 ◽  
Author(s):  
Agustin Barria ◽  
Rodrigo Marín-Nahuelpi ◽  
Pablo Cáceres ◽  
María E. López ◽  
Liane N. Bassini ◽  
...  
Keyword(s):  
Rainbow Trout ◽  
Oncorhynchus Mykiss ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Single Step ◽  
Genome Wide Association ◽  
Rainbow Trout Oncorhynchus Mykiss ◽  
Genome Wide ◽  
Piscirickettsia Salmonis

17 Genome-wide Association Study for Heat Stress Tolerance in Swine Using Weighted Single-step GBLUP

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 8-8
Author(s):  
Gabriella R Dodd ◽  
Breno O Fragomeni ◽  
Kent A Gray ◽  
Yijian Huang
Keyword(s):  
Heat Stress ◽  
Association Study ◽  
Stress Tolerance ◽  
Genetic Correlation ◽  
Genome Wide Association Study ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Heat Stress Tolerance ◽  
Genomic Regions

Abstract The purpose of this study was to perform a genome-wide association study to determine the genomic regions associated with heat stress tolerance in swine as well as analyze the accuracy of prediction. Phenotypic information on carcass weight was available for 227,043 individuals from commercial farms in North Carolina and Missouri. Individuals were a commercial cross of a Duroc sire and a dam resulting from a Landrace and Large White cross. Genotypic information was available for 8,232 animals with 33,581 SNP. The pedigree file contained 553,448 animals. A 78 on the Temperature Humidity Index (THI) was used as a threshold for heat stress. A two-trait analysis was used with the phenotypes heat stress (trait one) and non-heat stress (trait two). Variance components were calculated via AIREML and breeding values were calculated using single step GBLUP (ssGBLUP). The heritability for trait one and two were calculated at 0.25 and 0.20, respectively, and the genetic correlation was calculated as 0.63. Validation was calculated for 163 genotyped sires with progeny in the last generation. The GEBV of complete data was used as the benchmark, and the accuracy was determined as the correlation between the GEBV of the reduced and complete data for the validation sires. Weighted ssGBLUP did not increase the accuracies, both methods showed a maximum accuracy of 0.32 for trait one and 0.54 for trait two. Manhattan Plots for trait one, trait two, and the difference between the two were created from the results of the two-trait analysis. Windows explaining around 1% of the genetic variance were identified. The only difference between the two traits was a peak at chromosome 14. The genetic correlation suggests different mechanisms for growth under heat stress. The GWAS results show that both traits are highly polygenic, with few genomic regions explaining more than 1% of variance.

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