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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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Epistasis Analysis01:09

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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...
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Law of Independent Assortment02:03

Law of Independent Assortment

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While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.
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Overview
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Translation01:31

Translation

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Translation is the process of synthesizing proteins from the genetic information carried by messenger RNA (mRNA). Following transcription, it constitutes the final step in the expression of genes. This process is carried out by ribosomes, complexes of protein and specialized RNA molecules. Ribosomes, transfer RNA (tRNA), and other proteins produce a chain of amino acids—the polypeptide—as the end product of translation.
Translation Produces the Building Blocks of Life
Proteins are...
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Incomplete Dominance01:43

Incomplete Dominance

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Gregor Mendel's work (1822 - 1884) was primarily focused on pea plants. Through his initial experiments, he determined that every gene in a diploid cell has two variants called alleles inherited from each parent. He suggested that amongst these two alleles, one allele is dominant in character and the other recessive. The combination of alleles determines the phenotype of a gene in an organism.
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Related Experiment Video

Updated: Sep 26, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
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Transcriptome-wide association studies: a view from Mendelian randomization.

Huanhuan Zhu1, Xiang Zhou1,2

  • 1Department of Biostatistics, University of Michigan, Ann Arbor, MI 48109, USA.

Quantitative Biology (Beijing, China)
|April 18, 2022
PubMed
Summary
This summary is machine-generated.

This review reframes thirteen transcriptome-wide association studies (TWAS) methods as two-sample Mendelian randomization (MR) analyses. This perspective clarifies the benefits and pitfalls of TWAS for understanding gene regulatory mechanisms in complex traits.

Keywords:
expression mapping studiesgenome-wide association studiestranscriptome-wide association studies

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Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genomics

Background:

  • Genome-wide association studies (GWAS) identify genetic variants linked to complex traits, but biological mechanisms are often unclear.
  • Transcriptome-wide association studies (TWAS) integrate GWAS with expression data to explore gene regulatory mechanisms underlying these associations.
  • Numerous TWAS methods exist, each with distinct modeling assumptions and biological questions addressed, complicating theoretical understanding.

Purpose of the Study:

  • To provide a technical review of thirteen TWAS methods.
  • To re-interpret TWAS methods through the lens of Mendelian randomization (MR).
  • To offer a unified framework for understanding TWAS methodology.

Main Methods:

  • Systematic review of thirteen TWAS methodologies.
  • Framing TWAS as two-sample Mendelian randomization (MR) analysis.
  • Analysis of how GWAS and expression data features influence MR adaptation for TWAS.

Main Results:

  • All thirteen reviewed TWAS methods can be conceptualized as two-sample MR analyses.
  • The MR perspective offers a novel angle for understanding the strengths and limitations of various TWAS approaches.
  • Re-interpretation of modeling assumptions for different TWAS methods using an MR framework.

Conclusions:

  • This review serves as a valuable reference for TWAS methodologists and practitioners.
  • Understanding TWAS through MR enhances the interpretation of gene-trait associations.
  • Highlights future directions for developing advanced TWAS methodologies.