Modeling Complex Disease with Demographic and Environmental Covariates and a Candidate Gene Marker

2001 ◽  
Vol 21 (S1) ◽  
pp. S423-S428 ◽  
Author(s):  
Joseph Beyene ◽  
Shafagh Fallah ◽  
Shelley B. Bull ◽  
David Tritchler ◽  
Viann Chan ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Complex Disease ◽  
Gene Marker ◽  
Environmental Covariates

Candidate-gene association studies with pedigree data: Controlling for environmental covariates

2003 ◽  
Vol 24 (4) ◽  
pp. 273-283 ◽  
Author(s):  
S.L. Slager ◽  
D.J. Schaid ◽  
L. Wang ◽  
S.N. Thibodeau
Keyword(s):  
Candidate Gene ◽  
Association Studies ◽  
Pedigree Data ◽  
Environmental Covariates ◽  
Gene Association ◽  
Candidate Gene Association

Selection of Genes and Single Nucleotide Polymorphisms for Fine Mapping Starting From a Broad Linkage Region

2007 ◽  
Vol 10 (6) ◽  
pp. 871-885 ◽  
Author(s):  
An Windelinckx ◽  
Robert Vlietinck ◽  
Jeroen Aerssens ◽  
Gaston Beunen ◽  
Martine A. I. Thomis
Keyword(s):  
Linkage Disequilibrium ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Fine Mapping ◽  
Complex Disease ◽  
Gene Selection ◽  
Candidate Gene Approach ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Selection Of

AbstractFine mapping of linkage peaks is one of the great challenges facing researchers who try to identify genes and genetic variants responsible for the variation in a certain trait or complex disease. Once the trait is linked to a certain chromosomal region, most studies use a candidate gene approach followed by a selection of polymorphisms within these genes, either based on their possibility to be functional, or based on the linkage disequilibrium between adjacent markers. For both candidate gene selection and SNP selection, several approaches have been described, and different software tools are available. However, mastering all these information sources and choosing between the different approaches can be difficult and time-consuming. Therefore, this article lists several of these in silico procedures, and the authors describe an empirical two-step fine mapping approach, in which candidate genes are prioritized using a bioinformatics approach (ENDEAVOUR), and the top genes are chosen for further SNP selection with a linkage disequilibrium based method (Tagger). The authors present the different actions that were applied within this approach on two previously identified linkage regions for muscle strength. This resulted in the selection of 331 polymorphisms located in 112 different candidate genes out of an initial set of 23,300 SNPs.

Candidate gene marker associations with fatty acid profiles in heavy pigs

Meat Science ◽  
2013 ◽  
Vol 93 (3) ◽  
pp. 495-500 ◽  
Author(s):  
B. Renaville ◽  
A. Prandi ◽  
B. Fan ◽  
A. Sepulcri ◽  
M.F. Rothschild ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Candidate Gene ◽  
Gene Marker ◽  
Fatty Acid Profiles

Predicting Risk of Coronary Artery Disease from DNA Microarray-Based Genotyping Using Neural Networks and Other Statistical Analysis Tool

2003 ◽  
Vol 01 (03) ◽  
pp. 521-539 ◽  
Author(s):  
C. K. Tham ◽  
C. K. Heng ◽  
W. C. Chin
Keyword(s):  
Neural Networks ◽  
Coronary Artery Disease ◽  
Statistical Analysis ◽  
Coronary Artery ◽  
Complex Disease ◽  
Gene Marker ◽  
Analysis Tool ◽  
Novel Approach ◽  
Statistical Analysis Tool ◽  
Artery Disease

This paper presents a novel approach for complex disease prediction that we have developed, exemplified by a study on risk of coronary artery disease (CAD). This multi-disciplinary approach straddles fields of microarray technology and genetics, neural networks (NN), data mining and machine learning, as well as traditional statistical analysis techniques, namely principal components analysis (PCA) and factor analysis (FA). A description of the biological background of the study is given, followed by a detailed description of how the problem has been modeled for analyses by neural networks and FA. A committee learning approach for NN has been used to improve generalization rates. We show that our NN approach is able to yield promising prediction results despite using only the most fundamental network structures. More interestingly, through the statistical analysis process, genes of similar biological functions have been clustered. In addition, a gene marker involved in breaking down lipids has been found to be the most correlated to CAD.

scholarly journals NAC Candidate Gene Marker for bgm-1 and Interaction With QTL for Resistance to Bean Golden Yellow Mosaic Virus in Common Bean

2021 ◽  
Vol 12 ◽  
Author(s):  
Alvaro Soler-Garzón ◽  
Atena Oladzad ◽  
James Beaver ◽  
Stephen Beebe ◽  
Rian Lee ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Common Bean ◽  
Mosaic Virus ◽  
Genome Wide Association Study ◽  
Stop Codon ◽  
Genetic Resistance ◽  
Yellow Mosaic Virus ◽  
Gene Marker ◽  
Exon 2 ◽  
Golden Yellow

Genetic resistance is the primary means for control of Bean golden yellow mosaic virus (BGYMV) in common bean (Phaseolus vulgaris L.). Breeding for resistance is difficult because of sporadic and uneven infection across field nurseries. We sought to facilitate breeding for BGYMV resistance by improving marker-assisted selection (MAS) for the recessive bgm-1 gene and identifying and developing MAS for quantitative trait loci (QTL) conditioning resistance. Genetic linkage mapping in two recombinant inbred line populations and genome-wide association study (GWAS) in a large breeding population and two diversity panels revealed a candidate gene for bgm-1 and three QTL BGY4.1, BGY7.1, and BGY8.1 on independent chromosomes. A mutation (5 bp deletion) in a NAC (No Apical Meristem) domain transcriptional regulator superfamily protein gene Phvul.003G027100 on chromosome Pv03 corresponded with the recessive bgm-1 resistance allele. The five bp deletion in exon 2 starting at 20 bp (Pv03: 2,601,582) is expected to cause a stop codon at codon 23 (Pv03: 2,601,625), disrupting further translation of the gene. A Tm-shift assay marker named PvNAC1 was developed to track bgm-1. PvNAC1 corresponded with bgm-1 across ∼1,000 lines which trace bgm-1 back to a single landrace “Garrapato” from Mexico. BGY8.1 has no effect on its own but exhibited a major effect when combined with bgm-1. BGY4.1 and BGY7.1 acted additively, and they enhanced the level of resistance when combined with bgm-1. Tm-shift assay markers were generated for MAS of the QTL, but their effectiveness requires further validation.

Development of a candidate gene marker for Rf 1 based on a PPR gene in cytoplasmic male sterile CMS-D2 Upland cotton

2014 ◽  
Vol 34 (1) ◽  
pp. 231-240 ◽  
Author(s):  
Jianyong Wu ◽  
Xiuxia Cao ◽  
Liping Guo ◽  
Tingxiang Qi ◽  
Hailing Wang ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Upland Cotton ◽  
Gene Marker ◽  
Male Sterile ◽  
Cytoplasmic Male Sterile

A candidate gene study in predicted severe acute pancretitis

2001 ◽  
Vol 120 (5) ◽  
pp. A468-A468 ◽  
Author(s):  
G GALLAGHER ◽  
P CHONG ◽  
J ESKDALE ◽  
A COOK ◽  
S CAIMS ◽  
...  
Keyword(s):  
Candidate Gene ◽  
Candidate Gene Study ◽  
Gene Study ◽  
Acute Pancretitis
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