Abstract 1444: Weighted Gene Co-expression Network Analysis of Adipose and Liver Reveals Gene Modules Related to Plasma HDL Levels and Containing Candidate Genes at Loci Identified in Genome Wide Association Studies

Circulation ◽  
2008 ◽  
Vol 118 (suppl_18) ◽  
Author(s):  
Peter Langfelder ◽  
Margarete Mehrabian ◽  
Eric E Schadt ◽  
Aldons J Lusis ◽  
Steve Horvath
Keyword(s):  
Network Analysis ◽  
Association Studies ◽  
Expression Patterns ◽  
Screening Method ◽  
Functional Enrichment ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Gene Modules ◽  
Hdl Metabolism

The genetic and environmental factors contributing to HDL-cholesterol levels are highly complex. For example, a recent meta-analysis of three genome wide association studies (GWAS), consisting of over 9000 individuals, revealed several loci, but altogether these explained less than 10% of HDL variation. Since HDL has a heritability of about 50%, there clearly must be many as yet unidentified factors. To better address this complexity, we have utilized integrative genomic approaches to relate common DNA variation to gene networks and HDL metabolism. We report a Weighted Gene Co-expression Network Analysis (WGCNA) of genome-wide expression data from a CAST X C57BL6/J F2 intercross. WGCNA is a systems-based gene expression analysis and gene screening method. It utilizes co-expression patterns among genes to identify gene modules (groups of highly co-expressed genes) significantly associated with a clinical trait, in this case plasma HDL levels. Co-expression modules may represent cellular processes and interacting pathways that provide a bridge between individual genes and a systems-level view of the organism. A module-centric analysis effectively alleviates the multiple testing problems inherent in microarray data analysis and can be considered a biologically motivated data-reduction scheme. Using data from liver and adipose tissues, we have identified several modules strongly associated with plasma HDL levels (p-values ranging from below 1e-20 to 1e-5). Gene ontology and functional enrichment analysis indicate that these modules are indeed biologically meaningful. The modules contain variants of several genes under loci that were recently implicated by three GWA studies: liver modules include GCKR, ANGPTL4, ABCA3, APOA1, and APOA4, while the adipose modules include ABCA6, ANGPTL11 and 12, MMAB, MLXIPL, SORT1, PBX4, PLTP, and APOL6. Thus, our study also serves to help identify likely candidates from GWAS. In conclusion, applying WGCNA methods reveals modules that are biologically meaningful, statistically significant, and enriched for genes and pathways related to HDL metabolism and transport.

scholarly journals Adaptive growth homeostasis in response to drought in Iberian Arabidopsis accessions

2021 ◽  
Author(s):  
Ángel Ferrero-Serrano ◽  
Sarah M Assmann
Keyword(s):  
Leaf Area ◽  
Stress Responses ◽  
Association Studies ◽  
Transport Processes ◽  
Functional Enrichment ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Intrinsic Water Use Efficiency

Plants respond to environmental fluctuations through plastic phenotypic shifts. Whether a plastic response upon environmental variability is adaptive or not has been subject to debate. Using a set of Iberian Arabidopsis accessions, we quantified an interplay between passive plastic reductions in leaf areas that we found typical of accessions from productive environments and homeostatic leaf areas responses to drought typified by accessions originating from unproductive environments. Results from Genome-Wide Association Studies (GWAS) and Transcriptome Wide Association Studies (TWAS) highlight the role of auxin-related processes and, in particular, the possible role of the SMALL AUXIN UP RNA 26 (SAUR26) gene in the regulation of the observed plastic responses. Homeostatic responses in leaf area potential following drought were typical of accessions with lower leaf area potential under well-watered conditions. Transcripts that were negatively associated with leaf area potential and positively associated with homeostatic and positive leaf area plasticity following drought showed functional enrichment in ion transport processes. We hypothesized that the contrasting plastic and homeostatic responses in leaf area potential were associated with differential intrinsic water use efficiency (WUEi). We confirmed this relationship in a metanalysis conducted using previously published δ13C measurements. Our results highlight the adaptive role of homeostatic leaf area response to water depletion arising from increased WUEi. The concerted utilization of Genome-Wide Association Studies (GWAS), Transcriptome Wide Association Studies (TWAS), and expression Genome-Wide Association Studies (eGWAS) allows integration of phenotype, genotype, and transcript abundance to identify both "plasticity genes" and "homeostasis genes" associated with drought stress responses.

scholarly journals Identification of candidate genes underlying nodulation-specific phenotypes in Medicago truncotula through integration of genome-wide association studies and co-expression networks

2018 ◽  
Author(s):  
Jean-Michel Michno ◽  
Liana T. Burghardt ◽  
Junqi Liu ◽  
Joseph R. Jeffers ◽  
Peter Tiffin ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Medicago Truncatula ◽  
Association Studies ◽  
Expression Patterns ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
High Confidence ◽  
Functional Relationships ◽  
Genome Wide ◽  
Mapping Information

ABSTRACTGenome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination near each significant interval. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in Medicago truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.

scholarly journals Practical Issues in Screening and Variable Selection in Genome-Wide Association Analysis

2014 ◽  
Vol 13s7 ◽  
pp. CIN.S16350 ◽  
Author(s):  
Sungyeon Hong ◽  
Yongkang Kim ◽  
Taesung Park
Keyword(s):  
Variable Selection ◽  
Association Studies ◽  
Screening Method ◽  
Computational Cost ◽  
Penalized Regression ◽  
Adaptive Lasso ◽  
Genome Wide Association ◽  
Snp Analysis ◽  
Genome Wide Association Studies ◽  
Genome Wide

Variable selection methods play an important role in high-dimensional statistical modeling and analysis. Computational cost and estimation accuracy are the two main concerns for statistical inference from ultrahigh-dimensional data. In particular, genome-wide association studies (GWAS), which focus on identifying single nucleotide polymorphisms (SNPs) associated with a disease of interest, have produced ultrahigh-dimensional data. Numerous methods have been proposed to handle GWAS data. Most statistical methods have adopted a two-stage approach: pre-screening for dimensional reduction and variable selection to identify causal SNPs. The pre-screening step selects SNPs in terms of their P-values or the absolute values of the regression coefficients in single SNP analysis. Penalized regressions, such as the ridge, lasso, adaptive lasso, and elastic-net regressions, are commonly used for the variable selection step. In this paper, we investigate which combination of pre-screening method and penalized regression performs best on a quantitative phenotype using two real GWAS datasets.

scholarly journals Identification of Novel Genomic Variations in Susceptibility to Nonsyndromic Cleft Lip and Palate Patients

2021 ◽  
Vol 13 (4) ◽  
pp. 650-657
Author(s):  
Kapil Kumar Avasthi ◽  
Srinivasan Muthuswamy ◽  
Ambreen Asim ◽  
Amit Agarwal ◽  
Sarita Agarwal
Keyword(s):  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Association Studies ◽  
Genetic Variations ◽  
Functional Enrichment ◽  
Genome Wide Association ◽  
Regulatory Sequences ◽  
Genome Wide Association Studies ◽  
Medicine Research ◽  
Genome Wide

Background: Nonsyndromic cleft lip with or without palate (NSCL/P) is a multifactorial and common birth malformation caused by genetic and environmental factors, as well as by teratogens. Genome-wide association studies found genetic variations with modulatory effects of NSCL/P formation in Chinese and Iranian populations. We aimed to identify the susceptibility of single-nucleotide polymorphisms (SNPs) to nonsyndromic cleft lip with or without palate in the Indian population. Material and Methods: The present study was conducted on NSCL/P cases and controls. Genomic DNA was extracted from peripheral blood and Axiom- Precision Medicine Research Array (PMRA) was performed. The Axiom-PMRA covers 902,527 markers and several thousand novel risk variants. Quality control-passed samples were included for candidate genetic variation identification, gene functional enrichment, and pathway and network analysis. Results: The genome-wide association study identified fourteen novel candidate gene SNPs that showed the most significant association with the risk of NSCL/P, and eight were predicted to have regulatory sequences. Conclusion: The GWAS study showed novel candidate genetic variations in NSCL/P formations. These findings contribute to the understanding of genetic predisposition to nonsyndromic cleft lip with or without palate.

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