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Related Concept Videos

Epistasis Analysis01:09

Epistasis Analysis

Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Pharmacogenomics: Identification of New Drug Targets01:29

Pharmacogenomics: Identification of New Drug Targets

Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
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Pleiotropy01:33

Pleiotropy

Pleiotropy is the phenomenon in which a single gene impacts multiple, seemingly unrelated phenotypic traits. For example, defects in the SOX10 gene cause Waardenburg Syndrome Type 4, or WS4, which can cause defects in pigmentation, hearing impairments, and an absence of intestinal contractions necessary for elimination. This diversity of phenotypes results from the expression pattern of SOX10 in early embryonic and fetal development. SOX10 is found in neural crest cells that form melanocytes,...

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics
08:09

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Published on: June 17, 2012

An integrative modular approach to systematically predict gene-phenotype associations.

Michael R Mehan1, Juan Nunez-Iglesias, Chao Dai

  • 1Program in Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles CA 90089, USA. rielmeha@usc.edu

BMC Bioinformatics
|February 4, 2010
PubMed
Summary

Complex human diseases arise from multiple gene mutations. Our network approach identifies gene modules linked to specific phenotypes, revealing widespread gene pleiotropy and potential drug targets.

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Area of Science:

  • Genomics
  • Systems Biology
  • Bioinformatics

Background:

  • Complex human diseases often result from numerous mutations with small individual effects.
  • Studying the genetic basis of complex phenotypes requires understanding gene interactions and regulation.
  • A network-based approach can identify gene expression modules associated with specific phenotypes.

Purpose of the Study:

  • To develop and apply a network-based method for identifying phenotype-specific coexpression modules.
  • To predict novel human gene-phenotype associations using integrated biological data.
  • To analyze the prevalence of gene pleiotropy and its regulatory mechanisms in complex diseases.

Main Methods:

  • Integrated gene coexpression modules, protein-protein interactions, Gene Ontology annotations, and literature-derived gene-phenotype associations.
  • Applied the method to 338 microarray datasets across 178 phenotype classes.
  • Utilized random forest classifiers and ChIP-chip data for transcription factor binding analysis.

Main Results:

  • Identified 193,145 phenotype-specific coexpression modules and predicted 6,558 gene-phenotype associations.
  • Revealed that 40.9% of genes are pleiotropic, indicating a higher prevalence than previously thought.
  • Confirmed that dynamic transcriptional regulation drives the formation of phenotype-specific gene modules.

Conclusions:

  • Generated a genome-wide gene-to-phenotype map with implications for drug discovery and understanding disease.
  • Demonstrated a high prevalence of gene pleiotropy and suggested the role of phenotype-specific transcription factor binding in phenotypic diversity.
  • Made all study resources freely available via an online Phenotype Prediction Database.