scholarly journals Epistasis Detection in Genome-Wide Screening for Complex Human Diseases in Structured Populations

2019 ◽  
Vol 2 (1) ◽  
pp. 19-27
Author(s):  
Fentaw Abegaz ◽  
François Van Lishout ◽  
Jestinah M. Mahachie John ◽  
Kridsadakorn Chiachoompu ◽  
Archana Bhardwaj ◽  
...  
Keyword(s):  
Structured Populations ◽  
Human Diseases ◽  
Genome Wide

scholarly journals Erratum to: Genome-wide association mapping of agronomic and morphologic traits in highly structured populations of barley cultivars

2011 ◽  
Vol 124 (2) ◽  
pp. 247-247
Author(s):  
Minghui Wang ◽  
Ning Jiang ◽  
Tianye Jia ◽  
Lindsey Leach ◽  
James Cockram ◽  
...  
Keyword(s):  
Association Mapping ◽  
Structured Populations ◽  
Genome Wide Association ◽  
Barley Cultivars ◽  
Genome Wide

scholarly journals Genetics and epigenetics of syntropic diseases

2010 ◽  
Vol 8 (4) ◽  
pp. 39-43 ◽  
Author(s):  
Viktoriya N Gorbunova
Keyword(s):  
Association Studies ◽  
Structural Features ◽  
Human Diseases ◽  
Functional Polymorphisms ◽  
Genetic Components ◽  
Expression Control ◽  
Candidate Gene Association ◽  
Genome Wide ◽  
The Common ◽  
The Many

 The genetic components are involved in aetiology of the common human diseases. For most of them it is significant the phenomenon of syntropies — nonrandom combination of different diseases in the same patients. Three methodic approaches have been successfully used for the identification of genetic factors predisposed to the common human diseases: linkage analysis, candidate gene association studies (GASs) and genome-wide association scans (GWASs). The structural features of the many genes make a small but significant contribution to the overall risk of common diseases. Syntropy of related diseases is determined of having of share in disease pathogenesis the functional polymorphisms of genes controlling the same metabolic pathways. Nonrandom combination of different diseases in the same patients is determined of common epigenetic mechanisms involved in expression control of different «gene nets» disorder.

scholarly journals Gene-centric functional dissection of human genetic variation uncovers regulators of hematopoiesis

2018 ◽  
Author(s):  
Satish K Nandakumar ◽  
Sean K McFarland ◽  
Laura Marlene Mateyka ◽  
Caleb A Lareau ◽  
Jacob C Ulirsch ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Target Genes ◽  
Association Studies ◽  
Human Diseases ◽  
Genome Wide Association Studies ◽  
Loss Of Function ◽  
Genome Wide ◽  
Causal Variants ◽  
Genomic Regions

Genome-wide association studies (GWAS) have identified thousands of variants associated with human diseases and traits. However, the majority of GWAS-implicated variants are in non-coding genomic regions and require in depth follow-up to identify target genes and decipher biological mechanisms. Here, rather than focusing on causal variants, we have undertaken a pooled loss-of-function screen in primary hematopoietic cells to interrogate 389 candidate genes contained in 75 loci associated with red blood cell traits. Using this approach, we identify 77 genes at 38 GWAS loci, with most loci harboring 1-2 candidate genes. Importantly, the hit set was strongly enriched for genes validated through orthogonal genetic approaches. Genes identified by this approach are enriched in relevant biological pathways, allowing regulators of human erythropoiesis and blood disease modifiers to be defined. More generally, this functional screen provides a paradigm for gene-centric follow up of GWAS for a variety of human diseases and traits.

scholarly journals A fast linkage disequilibrium-based statistical test for Genome-Wide Epistatic Selection Scans in structured populations

2020 ◽  
Author(s):  
Léa Boyrie ◽  
Corentin Moreau ◽  
Florian Frugier ◽  
Christophe Jacquet ◽  
Maxime Bonhomme
Keyword(s):  
Population Structure ◽  
Linkage Disequilibrium ◽  
Experimental Evidence ◽  
Medicago Truncatula ◽  
Genetic Interaction ◽  
Correlation Coefficients ◽  
Statistical Test ◽  
Structured Populations ◽  
Snp Data ◽  
Genome Wide

AbstractThe quest for genome-wide signatures of selection in populations using SNP data has proven efficient to uncover genes involved in conserved or adaptive molecular functions, but none of the statistical methods were designed to identify interacting genes as targets of selective processes. Here, we propose a straightforward statistical test aimed at detecting epistatic selection, based on a linkage disequilibrium (LD) measure accounting for population structure and heterogeneous relatedness between individuals. SNP-based (Trv) and window-based (TcorPC1v) statistics fit a Student distribution, allowing to easily and quickly test the significance of correlation coefficients in the frame of Genome-Wide Epistatic Selection Scans (GWESS) using candidate genes as baits. As a proof of concept, use of SNP data from the Medicago truncatula symbiotic legume plant uncovered a previously unknown gene coadaptation between the MtSUNN (Super Numeric Nodule) receptor and the MtCLE02 (CLAVATA3-Like) signalling peptide, and experimental evidence accordingly supported a MtSUNN-dependent negative role of MtCLE02 in symbiotic root nodulation. Using human HGDP-CEPH SNP data, our new statistical test uncovered strong LD between SLC24A5 and EDAR worldwide, which persists after correction for population structure and relatedness in Central South Asian populations. This result suggests adaptive genetic interaction or coselection between skin pigmentation and the ectodysplasin pathway involved in the development of ectodermal organs (hairs, teeth, sweat glands), in some human populations. Applying this approach to genome-wide SNP data will foster the identification of evolutionary coadapted gene networks.Author summaryPopulation genomic methods have allowed to identify many genes associated with adaptive processes in populations with complex histories. However, they are not designed to identify gene coadaptation between genes through epistatic selection, in structured populations. To tackle this problem, we developed a straightforward LD-based statistical test accounting for population structure and heterogeneous relatedness between individuals, using SNP-based (Trv) or windows-based (TcorPC1v) statistics. This allows easily and quickly testing for significance of correlation coefficients between polymorphic loci in the frame of Genome Wide Epistatic Selection Scans (GWESS). Following detection of gene coadaptation using SNP data from human and the model plant Medicago truncatula, we report experimental evidence of genetic interaction between two receptors involved in the regulation of root nodule symbiosis in Medicago truncatula. This test opens new avenues for exploring the evolution of genes as interacting units and thus paves the way to infer new networks based on evolutionary coadaptation between genes.

scholarly journals The interplay between host genetics and the gut microbiome reveals common and distinct microbiome features for complex human diseases

2020 ◽  
Author(s):  
Fengzhe Xu ◽  
Yuanqing Fu ◽  
Tingyu Sun ◽  
Zengliang Jiang ◽  
Zelei Miao ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Lupus Erythematosus ◽  
Gut Microbiome ◽  
Genome Wide Association Study ◽  
Human Diseases ◽  
Host Genetics ◽  
Genome Wide ◽  
Disease Aetiology ◽  
Significant Heritability ◽  
Host Genetic

Abstract Background Interest in the interplay between host genetics and the gut microbiome in complex human diseases is increasing, with prior evidence mainly being derived from animal models. In addition, the shared and distinct microbiome features among complex human diseases remain largely unclear.Results This analysis was based on a Chinese population with 1,475 participants. We estimated the SNP-based heritability, which suggested that Desulfovibrionaceae and Odoribacter had significant heritability estimates (0.456 and 0.476, respectively). We performed a microbiome genome-wide association study to identify host genetic variants associated with the gut microbiome. We then conducted bidirectional Mendelian randomization analyses to examine the potential causal associations between the gut microbiome and complex human diseases. We found that Saccharibacteria could potentially decrease the concentration of serum creatinine and increase the estimated glomerular filtration rate. On the other hand, atrial fibrillation, chronic kidney disease and prostate cancer, as predicted by host genetics, had potential causal effects on the abundance of some specific gut microbiota. For example, atrial fibrillation increased the abundance of Burkholderiales and Alcaligenaceae and decreased the abundance of Lachnobacterium, Bacteroides coprophilus, Barnesiellaceae, undefined genus in family Veillonellaceae and Mitsuokella. Further disease-microbiome feature analysis suggested that systemic lupus erythematosus and chronic myeloid leukaemia shared common gut microbiome features.Conclusions These results suggest that different complex human diseases share common and distinct gut microbiome features, which may help reshape our understanding of disease aetiology in humans.

scholarly journals A linkage disequilibrium-based statistical test for Genome-Wide Epistatic Selection Scans in structured populations

Heredity ◽  
2020 ◽  
Vol 126 (1) ◽  
pp. 77-91
Author(s):  
Léa Boyrie ◽  
Corentin Moreau ◽  
Florian Frugier ◽  
Christophe Jacquet ◽  
Maxime Bonhomme
Keyword(s):  
Linkage Disequilibrium ◽  
Statistical Test ◽  
Structured Populations ◽  
Genome Wide

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.

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