Comparison of Likelihood Approaches for Combined Segregation and Linkage Analysis of a Complex Disease and a Candidate Gene Marker Under Different Ascertainment Schemes

2001 ◽  
Vol 21 (S1) ◽  
pp. S760-S765 ◽  
Author(s):  
Maria Martinez ◽  
Alisa M. Goldstein ◽  
Jeffrey R. O'Connell
Keyword(s):  
Linkage Analysis ◽  
Candidate Gene ◽  
Complex Disease ◽  
Gene Marker

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

scholarly journals Combined bulked segregant sequencing and traditional linkage analysis for identification of candidate gene for purple leaf sheath in maize

PLoS ONE ◽  
2018 ◽  
Vol 13 (1) ◽  
pp. e0190670 ◽  
Author(s):  
Pengcheng Li ◽  
Cancan Du ◽  
Yingying Zhang ◽  
Shuangyi Yin ◽  
Enying Zhang ◽  
...  
Keyword(s):  
Linkage Analysis ◽  
Candidate Gene ◽  
Leaf Sheath ◽  
Purple Leaf

Abstract 1743: Identification of a Novel Susceptibility Locus at 9q21 for Familial Bicuspid Aortic Valve Disease

Circulation ◽  
2007 ◽  
Vol 116 (suppl_16) ◽  
Author(s):  
Stephen H McKellar ◽  
Marineh Yagubyan ◽  
Ramanath Majumdar ◽  
David J Tester ◽  
Mariza de Andrade ◽  
...  
Keyword(s):  
Aortic Valve ◽  
Linkage Analysis ◽  
Microsatellite Markers ◽  
Candidate Gene ◽  
Candidate Genes ◽  
Bicuspid Aortic Valve ◽  
Fine Mapping ◽  
Aortic Valve Disease ◽  
Biological Plausibility ◽  
Genome Wide

Background: Bicuspid aortic valve disease (BAV), the most common congenital cardiovascular malformation, has an incidence of 0.5–1.0% of live births. While most cases of BAV appear to be sporadic, familial inheritance patterns have been observed consistent with autosomal dominant inheritance with variable penetrance. However, little is known about specific genetic loci responsible for familial BAV. Here, we performed linkage analysis on a large multi-generational pedigree affected with BAV. Methods: We identified a large, five-generation pedigree (136 family members) with 10 individuals having BAV. Two-dimensional echocardiography was used to assign aortic valve phenotype. Genome-wide linkage analysis using 430 microsatellite markers (Marshfield Clinic) and fine mapping using 100 single nucleotide polymorphisms (Affymetrix) on chromosome 9 was performed on genomic DNA from all available family members. Logarithm of odds (LOD) scores of >2.0 were considered suggestive of linkage. Comprehensive splice site/open reading frame mutational analysis of candidate genes residing in the putative locus is underway using PCR, DHPLC, and DNA sequencing. A candidate gene, KLF9, Krüppel-like factor 9 was analyzed for mutations because of its role in cardiogenesis. Results: Multi-point genome-wide linkage analysis demonstrated a 7 cM region on chromosome 9q21 that was suggestive of linkage for familial BAV with a maximum multipoint LOD score of 2.8 flanked by the microsatellite markers GATA7D12 and D9S1834. This region contains several candidate genes with biological plausibility for BAV phenotype. KLF9- encoded Krüppel-like factor 9, localized to chromosome 9q21, was targeted as a prime candidate gene for familial BAV. However, no mutations involving the translated exons of KLF9 were detected. Further fine mapping studies and candidate gene analysis are currently underway. Conclusions: We report a novel susceptibility locus on chromosome 9q21 for BAV in a large multi-generational family. Although coding region mutations in KLF9 are not responsible for BAV in this pedigree, several candidate genes with biological plausibility for the development of congenital BAV lie within this region and warrant further scrutiny.

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.

scholarly journals Using Genomic Resources for Linkage Analysis in Peromyscus with an Application for Characterizing Dominant Spot

2020 ◽  
Author(s):  
Zhenhua Shang ◽  
David J Horovitz ◽  
Ronald H McKenzie ◽  
Jessica L Keisler ◽  
Michael R Felder ◽  
...  
Keyword(s):  
Linkage Analysis ◽  
Neural Crest ◽  
Candidate Gene ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Cholesterol Metabolism ◽  
Deer Mouse ◽  
Genomic Resources ◽  
Hybrid Offspring ◽  
Gene Regulatory

Abstract Background: Peromyscus are the most common mammalian species in North America and are widely used in both laboratory and field studies. The deer mouse, P. maniculatus and the old-field mouse, P. polionotus, are closely related and can generate viable and fertile hybrid offspring. The ability to generate hybrid offspring, coupled with developing genomic resources, enables researchers to conduct linkage analysis studies to identify genomic loci associated with specific traits. Results: We used available genomic data to identify DNA polymorphisms between P. maniculatus and P. polionotus and used the polymorphic data to identify the range of genetic complexity that underlies physiological and behavioral differences between the species, including cholesterol metabolism and genes associated with autism. In addition, we used the polymorphic data to conduct a candidate gene linkage analysis for the Dominant spot trait and determined that Dominant spot is linked to a region of chromosome 20 that contains a strong candidate gene, Sox10. During the linkage analysis, we found that the spot size varied quantitively in affected Peromyscus based on genetic background. Conclusions: The expanding genomic resources for Peromyscus facilitate their use in linkage analysis studies, enabling the identification of loci associated with specific traits. More specifically, we have linked a coat color spotting phenotype, Dominant spot, with Sox10, a member the neural crest gene regulatory network, and that there are likely two genetic modifiers that interact with Dominant spot. These results establish Peromyscus as a model system for identifying new alleles of the neural crest gene regulatory network.

scholarly journals Linkage analysis of the genetic determinants of T-cell IL-4 secretion, and identification of Flj20274 as a putative candidate gene

2005 ◽  
Vol 6 (4) ◽  
pp. 290-297 ◽  
Author(s):  
P Choi ◽  
D Xanthaki ◽  
S J Rose ◽  
M Haywood ◽  
H Reiser ◽  
...  
Keyword(s):  
T Cell ◽  
Linkage Analysis ◽  
Candidate Gene ◽  
Genetic Determinants ◽  
Putative Candidate Gene

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.

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