Introduction

  • An expression quantitative trait locus (eQTL) explains part of the variation in gene expression.
  • Traditional linkage and association mapping can be applied to gene expression traits (transcripts).
  • Genetic variants, such as single nucleotide polymorphisms (SNPs), that underlie eQTL illuminate transcriptional regulation and variation.

  • Many GWAS studies identify SNPs which to no lie within coding regions of the genome.
  • This implies that the SNPs lie within regulatory sequences which affect gene expression levels.
  • Merging gene expression with physiological trait QTL mapping can help to identify genes which affect physiological trait variation.

Load and Explore Data

  • It is important to inspect the phenotype distributions and to transform them to be nearly normal.

Mapping A Single Gene Expression Trait

  • Gene expression values must be normalized to account for the library size of each sample.
  • After normalization, gene expression values can be rankZ transformed to make the distribution of every gene the same.

Mapping Many Gene Expression Traits

  • Mapping all genes in a study requires a computing cluster.
  • Genes may have more than one QTL peak.
  • High LOD scores often occur only once per gene.

Maximum eQTL Peaks and Nearby Genes

  • There can be more than one significant QTL peak for each gene.
  • We sometimes focus on the largest peak for each gene.
  • A multiple-testing correction should be applied to all peaks.
  • Sometimes a gene s co-located with its QTL peak.

Creating A Transcriptome Map

  • Transcriptome maps aid in understanding gene expression regulation.
  • Local eQTL occur more frequently than distant eQTL.
  • Local eQTL appear along the diagonal in a transcriptome map and distant eQTL appear on the off-diagonal.
  • Stacks of eQTL which appear over a single locus are called eQTL hotspots and represent sets of genes which are transcriptionally regulated by a single locus.
  • The first principal component of genes in and eQTL hotspot can be used to summarize the genes in the hotspot.

Mediation Analysis

  • Mediation analysis investigates an intermediary between an independent variable and its effect on a dependent variable.
  • Mediation analysis is used in high-throughput genomics studies to identify molecular phenotypes, such as gene expression or methylation traits, that mediate the effect of genetic variation on disease phenotypes or other outcomes of interest.