Bayes Factor-Based Regulatory Gene Network Analysis of Genome-Wide Association Study of Economic Traits in a Purebred Swine Population

: Early stage prediction of economic trait performance is important and directly linked to profitability of farm pig production. Genome-wide association study (GWAS) has been applied to find causative genomic regions of traits. This study established a regulatory gene network using GWAS for critical economic pig characteristics, centered on easily measurable body fat thickness in live animals. We genotyped 2,681 pigs using Illumina Porcine SNP60, followed by GWAS to calculate Bayes factors for 47,697 single nucleotide polymorphisms (SNPs) of seven traits. Using this information, SNPs were annotated with specific genes near genome locations to establish the association weight matrix. The entire network consisted of 226 nodes and 6,921 significant edges. For in silico validation of their interactions, we conducted regulatory sequence analysis of predicted target genes of transcription factors (TFs). Three key regulatory TFs were identified to guarantee maximum coverage: AT-rich interaction domain 3B (ARID3B), glial cell missing homolog 1 (GCM1), and GLI family zinc finger 2 (GLI2). We identified numerous genes targeted by ARID3B, associated with cellular processes. GCM1 and GLI2 were involved in developmental processes, and their shared target genes regulated multicellular organismal process. This system biology-based function analysis might contribute to enhancing understanding of economic pig traits.

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Regulatory gene network from a genome-wide association study for sow lifetime productivity traits

Animal Genetics ◽

10.1111/age.12640 ◽

2018 ◽

Vol 49 (3) ◽

pp. 254-258 ◽

Cited By ~ 3

Author(s):

J.-H. Kang ◽

E.-A. Lee ◽

K.-C. Hong ◽

J.-M. Kim

Keyword(s):

Association Study ◽

Gene Network ◽

Genome Wide Association Study ◽

Regulatory Gene ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome

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Variants at the MHC Region Associate With Susceptibility to Clostridioides difficile Infection: A Genome-Wide Association Study Using Comprehensive Electronic Health Records

Frontiers in Immunology ◽

10.3389/fimmu.2021.638913 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jiang Li ◽

Yanfei Zhang ◽

Alexandria L. Jilg ◽

Donna M. Wolk ◽

Harshit S. Khara ◽

...

Keyword(s):

Association Study ◽

Target Genes ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Electronic Health Record Data ◽

Potential Target ◽

Clostridioides Difficile ◽

Genome Wide ◽

A Genome ◽

Electronic Health

BackgroundClostridioides difficile is a major cause of healthcare-associated and community-acquired diarrhea. Host genetic susceptibility to Clostridioides difficile infection has not been studied on a large-scale.MethodsA total of 1,160 Clostridioides difficile infection cases and 15,304 controls were identified by applying the eMERGE Clostridioides difficile infection algorithm to electronic health record data. A genome-wide association study was performed using a linear mixed model, adjusted for significant covariates in the full dataset and the antibiotic subgroup. Colocalization and MetaXcan were performed to identify potential target genes in Clostridioides difficile infection - relevant tissue types.ResultsNo significant genome-wide association was found in the meta-analyses of the full Clostridioides difficile infection dataset. One genome-wide significant variant, rs114751021, was identified (OR = 2.42; 95%CI = 1.84-3.11; p=4.50 x 10-8) at the major histocompatibility complex region associated with Clostridioides difficile infection in the antibiotic group. Colocalization and MetaXcan identified MICA, C4A/C4B, and NOTCH4 as potential target genes. Down-regulation of MICA, upregulation of C4A and NOTCH4 was associated with a higher risk for Clostridioides difficile infection.ConclusionsLeveraging the EHR and genetic data, genome-wide association, and fine-mapping techniques, this study identified variants and genes associated with Clostridioides difficile infection, provided insights into host immune mechanisms, and described the potential for novel treatment strategies for Clostridioides difficile infection. Future replication and functional validation are needed.

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