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Related Experiment Video

Updated: Jun 18, 2026

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

Comparing quantitative trait Loci and gene expression data.

Bing Han¹, Naomi S Altman, Jessica A Mong

¹RAND Corporation, Santa Monica, CA 90407, USA.

Advances in Bioinformatics

|November 19, 2009

Summary

This summary is machine-generated.

We developed new methods to compare gene locations from quantitative trait loci (QTL) and microarray data for addictive behavior. Chromosomes 2 and 16 show potential links to addictive behaviors in mice.

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An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

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Published on: November 3, 2010

Analyzing Multifactorial RNA-Seq Experiments with DiCoExpress

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Single-cell Gene Expression Profiling Using FACS and qPCR with Internal Standards

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Published on: February 25, 2017

Area of Science:

Genetics
Neuroscience
Bioinformatics

Background:

Quantitative trait loci (QTL) analysis identifies genomic regions associated with traits.
Microarray experiments identify gene expression patterns.
Understanding the genetic basis of addictive behavior is crucial.

Purpose of the Study:

To develop and apply statistical methods for comparing QTL positions with gene sets from other analyses.
To investigate the overlap between QTL for addictive behavior in mice and upregulated genes in the nucleus accumbens (NA).

Main Methods:

Development of statistical methods to compare genomic positions of QTL and gene sets.
Application of methods to mouse models of addictive behavior.
Analysis of genes upregulated in the nucleus accumbens (NA).

Main Results:

No significant overall association found between addictive behavior QTL and NA-upregulated genes.
Strong associations identified on chromosomes 2 and 16, suggesting potential links to addictive behavior.
The developed statistical methodology can assess mutual information between microarray and QTL analyses.

Conclusions:

While no broad overlap was detected, specific chromosomes (2 and 16) show promise for further investigation into the genetics of addiction.
The novel statistical framework is applicable to integrating diverse genomic datasets for trait association studies.