scholarly journals A novel strategy for detecting multiple loci in Genome-Wide Association Studies of complex diseases

2008 ◽  
Vol 4 (2) ◽  
pp. 150 ◽  
Author(s):  
Jing Li
Keyword(s):  
Association Studies ◽  
Complex Diseases ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Loci ◽  
Genome Wide ◽  
Novel Strategy

Identification of Critical Core Genes of Sarcoma Based on Centrality Analysis of Networks Nodes

2020 ◽  
Vol 10 (7) ◽  
pp. 1776-1784
Author(s):  
Shudong Wang ◽  
Jixiao Wang ◽  
Xinzeng Wang ◽  
Yuanyuan Zhang ◽  
Tao Yi
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Complex Diseases ◽  
Enrichment Analysis ◽  
Gene Interaction ◽  
Core Gene ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Gene Set ◽  
Genome Wide

Genome-wide association studies (GWAS) are powerful tools for identifying pathogenic genes of complex diseases and revealing genetic structure of diseases. However, due to gene-to-gene interactions, only a part of the hereditary factors can be revealed. The meta-analysis based on GWAS can integrate gene expression data at multiple levels and reveal the complex relationship between genes. Therefore, we used meta-analysis to integrate GWAS data of sarcoma to establish complex networks and discuss their significant genes. Firstly, we established gene interaction networks based on the data of different subtypes of sarcoma to analyze the node centralities of genes. Secondly, we calculated the significant score of each gene according to the Staged Significant Gene Network Algorithm (SSGNA). Then, we obtained the critical gene set HYC of sarcoma by ranking the scores, and then combined Gene Ontology enrichment analysis and protein network analysis to further screen it. Finally, the critical core gene set Hcore containing 47 genes was obtained and validated by GEPIA analysis. Our method has certain generalization performance to the study of complex diseases with prior knowledge and it is a useful supplement to genome-wide association studies.

scholarly journals Genome-Wide Association Studies: Progress in Identifying Genetic Biomarkers in Common, Complex Diseases

2007 ◽  
Vol 2 ◽  
pp. 117727190700200 ◽  
Author(s):  
Stephen F. Kingsmore ◽  
Ingrid E. Lindquist ◽  
Joann Mudge ◽  
William D. Beavis
Keyword(s):  
Genetic Heterogeneity ◽  
Complex Traits ◽  
Biomarker Discovery ◽  
Association Studies ◽  
Complex Diseases ◽  
Human Diseases ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Biomarkers ◽  
Genome Wide

Novel, comprehensive approaches for biomarker discovery and validation are urgently needed. One particular area of methodologic need is for discovery of novel genetic biomarkers in complex diseases and traits. Here, we review recent successes in the use of genome wide association (GWA) approaches to identify genetic biomarkers in common human diseases and traits. Such studies are yielding initial insights into the allelic architecture of complex traits. In general, it appears that complex diseases are associated with many common polymorphisms, implying profound genetic heterogeneity between affected individuals.

scholarly journals Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function

2009 ◽  
Vol 42 (1) ◽  
pp. 45-52 ◽  
Author(s):  
Dana B Hancock ◽  
Mark Eijgelsheim ◽  
Jemma B Wilk ◽  
Sina A Gharib ◽  
Laura R Loehr ◽  
...  
Keyword(s):  
Pulmonary Function ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Multiple Loci ◽  
Genome Wide ◽  
Meta Analyses

scholarly journals Genome-Wide Association Studies for Milk Somatic Cell Score in Romanian Dairy Cattle

Genes ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1495
Author(s):  
Daniela Elena Ilie ◽  
Alexandru Eugeniu Mizeranschi ◽  
Ciprian Valentin Mihali ◽  
Radu Ionel Neamț ◽  
George Vlad Goilean ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Somatic Cell ◽  
Association Studies ◽  
Somatic Cell Score ◽  
The Body ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Cattle Breeds ◽  
Multiple Loci ◽  
Genome Wide

Mastitis is one of the most frequently encountered diseases in dairy cattle, negatively affecting animal welfare and milk production. For this reason, contributions to understanding its genomic architecture are of great interest. Genome-wide association studies (GWAS) have identified multiple loci associated with somatic cell score (SCS) and mastitis in cattle. However, most of the studies have been conducted in different parts of the world on various breeds, and none of the investigations have studied the genetic architecture of mastitis in Romanian dairy cattle breeds up to this point in time. In this study, we report the first GWAS for SCS in dairy cattle breeds from Romania. For GWAS, we used an Axiom Bovine v3 SNP-chip (>63,000 Single Nucleotide Polymorphism -SNPs) and 33,330 records from 690 cows belonging to Romanian Spotted (RS) and Romanian Brown (RB) cattle. The results found one SNP significantly associated with SCS in the RS breed and 40 suggestive SNPs with −log10 (p) from 4 to 4.9 for RS and from 4 to 5.4 in RB. From these, 14 markers were located near 12 known genes (AKAP8, CLHC1, MEGF10, SATB2, GATA6, SPATA6, COL12A1, EPS8, LUZP2, RAMAC, IL12A and ANKRD55) in RB cattle, 3 markers were close to ZDHHC19, DAPK1 and MMP7 genes, while one SNP overlapped the HERC3 gene in RS cattle. Four genes (HERC3, LUZP2, AKAP8 and MEGF10) associated with SCS in this study were previously reported in different studies. The most significant SNP (rs110749552) associated with SCS was located within the HERC3 gene. In both breeds, the SNPs and position of association signals were distinct among the three parities, denoting that mastitis is controlled by different genes that are dependent according to parity. The current results contribute to an expansion in the body of knowledge regarding the proportion of genetic variability explained by SNPs for SCS in dairy cattle.

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