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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
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Regulation of Expression at Multiple Steps01:23

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The gene expression in cells is regulated at different stages: (i) transcription, (ii) RNA processing, (iii) RNA localization, and (iv) translation. Transcriptional regulation is mediated by regulatory proteins such as transcription factors, activators, or repressors—these control gene expression by initiating or inhibiting the transcription of genes. Once a precursor or pre-mRNA is produced, it undergoes post-transcriptional modification, including 5' capping, splicing, and the...
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Single Nucleotide Polymorphisms-SNPs01:05

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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...
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Ribosome Profiling

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Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
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Related Experiment Video

Updated: Jun 7, 2025

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
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TIPS: a novel pathway-guided joint model for transcriptome-wide association studies.

Neng Wang1,2, Zhenyao Ye3, Tianzhou Ma2

  • 1Department of Mathematics, University of Maryland, College Park, MD 20742, United States.

Briefings in Bioinformatics
|November 16, 2024
PubMed
Summary

This study introduces TIPS, a new method for analyzing complex traits by integrating gene pathways. TIPS identifies key genes and pathways associated with traits like blood pressure and brain aging, offering deeper biological insights than traditional methods.

Keywords:
EM algorithmbiological pathwayssparse group lassotranscriptome-wide association studies

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Area of Science:

  • Genomics and Bioinformatics
  • Statistical Genetics
  • Complex Trait Analysis

Background:

  • Genome-wide association studies (GWAS) identify single nucleotide polymorphisms (SNPs) associated with diseases, but many are in non-coding regions, hindering interpretation.
  • Transcriptome-wide association studies (TWAS) improve interpretability by linking SNPs to gene expression but often yield lists of genes lacking clear biological themes.
  • Univariate TWAS struggles to reveal underlying biological mechanisms for complex polygenic traits.

Purpose of the Study:

  • To develop a novel multivariate TWAS method, TIPS (Transcriptome-wide Imputation incorporating Pathway or gene Set information), for identifying genes and pathways associated with complex polygenic traits.
  • To improve the biological interpretability of TWAS findings by incorporating pathway information directly into the association model.
  • To enhance the identification of biologically relevant pathways and genes that may be missed by traditional univariate TWAS.

Main Methods:

  • Developed a multivariate TWAS method (TIPS) that jointly models imputation and association steps.
  • Incorporated a sparse group lasso penalty to enable simultaneous selection at both gene and pathway levels.
  • Utilized an expectation-maximization algorithm for parameter estimation in the penalized likelihood model.

Main Results:

  • Applied TIPS to complex traits including systolic blood pressure, diastolic blood pressure, and white matter brain age gap in UK Biobank data.
  • Identified critical, biologically relevant pathways and genes associated with these traits that were undetectable by traditional univariate TWAS combined with pathway enrichment analysis.
  • Simulations demonstrated that TIPS outperforms established TWAS methods in feature selection, statistical power, and prediction accuracy across various heritability and genetic architecture scenarios.

Conclusions:

  • TIPS offers a powerful approach for dissecting the genetic architecture of complex polygenic traits by integrating gene expression and pathway information.
  • The method enhances the discovery of biologically meaningful pathways and genes, providing deeper insights into trait-associated mechanisms.
  • TIPS represents a significant advancement over univariate TWAS, offering improved performance and interpretability for complex trait genetics.