scholarly journals Genome wide association study for heat stress induced mortality in a white egg layer line

2019 ◽  
Vol 98 (1) ◽  
pp. 92-96 ◽  
Author(s):  
A. Wolc ◽  
J. Arango ◽  
P. Settar ◽  
J.E. Fulton ◽  
N.P. O’Sullivan ◽  
...  
Keyword(s):  
Heat Stress ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Layer Line ◽  
Genome Wide

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.

A genome-wide association study of heat stress-associated SNPs in catfish

2016 ◽  
Vol 48 (2) ◽  
pp. 233-236 ◽  
Author(s):  
Y. Jin ◽  
T. Zhou ◽  
X. Geng ◽  
S. Liu ◽  
A. Chen ◽  
...  
Keyword(s):  
Heat Stress ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
A Genome

Genome wide association study on memory in schizophrenia patients and unaffected probands

2009 ◽  
Vol 42 (05) ◽  
Author(s):  
B Konte ◽  
I Giegling ◽  
AM Hartmann ◽  
H Konnerth ◽  
P Muglia ◽  
...  
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide

1701-P: Genome-Wide Association Study Identifies Novel Potential Associations with Birth Weight in a Southwestern American Indian Population

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 1701-P
Author(s):  
LAUREN E. WEDEKIND ◽  
WEN-CHI HSUEH ◽  
SAYUKO KOBES ◽  
MUIDEEN T. OLAIYA ◽  
WILLIAM C. KNOWLER ◽  
...  
Keyword(s):  
Birth Weight ◽  
American Indian ◽  
Association Study ◽  
Indian Population ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
American Indian Population ◽  
Genome Wide

The First Genome-Wide Association Study (GWAS) for Type 2 Diabetes in Youth from the Progress in Diabetes Genetics in Youth (ProDiGY) Collaboration

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1703-P ◽  
Author(s):  
SHYLAJA SRINIVASAN ◽  
JENNIFER TODD ◽  
LING CHEN ◽  
JASMIN DIVERS ◽  
SAM GIDDING ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Diabetes Genetics ◽  
Diabetes In Youth
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