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Genetic Analysis of Genome-wide Variation in Human Gene Expression Morley M. et al. Nature 2004,430: 743-747 . PowerPoint Presentation
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Genetic Analysis of Genome-wide Variation in Human Gene Expression Morley M. et al. Nature 2004,430: 743-747 . . Yen-Yi Ho. Outline. Introduction Data Method: Linkage analysis Results Discussion Comments. Introduction.

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slide1

Genetic Analysis of Genome-wide Variation in Human Gene ExpressionMorley M. et al. Nature 2004,430: 743-747.

Yen-Yi Ho

outline
Outline
  • Introduction
  • Data
  • Method: Linkage analysis
  • Results
  • Discussion
  • Comments
goal identify loci associated with variation in expression levels
Goal : Identify loci associated with variation in expression levels

Nucleus

regulators

Genomic DNA

mRNA

mRNA

Target

cis and t rans regulation

Trans-regulator

Cis-regulator

Cis and Trans regulation

Target gene expression phenotype

slide6
Data

Centre d'Etude du Polymorphisme Humain (CEPH) families are Utah residents with ancestry from northern and western Europe.

  • 14 families with genotype and expression data available for all parents and a mean of eight offspring (range 7-9)
slide7
2,756 autosomal SNP genetic loci (100kb within cluster, 3 Mb between cluster).
  • Gene expression phenotypes

~8,500 gene expression phenotypes in immortalized B cells using Affymetrix Genome Focus Array.

Expression intensity was scaled to 500 and transformed by log2.

slide8
3,554 most variable expression phenotypes are selected (between > within variation).
  • Using CEPH unrelated individuals (94 grandparents), two array replicates per individual was performed. The within individual variation was indicated by the mean of variance of array replicates.
method linkage analysis

A1 A2  A3 A4

A1 A2  A3 A4

A1 A2  A3A4

A1 A3 A1 A4

A1 A3 A2 A4

A1 A3 A1 A3

IBD=2

Method: Linkage analysis

IBD=1

IBD=0

IBD: identical-by-descent

slide11

15 10 5

For a particular target gene expression

t-statistics

SNP1 2 3 4 5 Genetic Locus

results
Results

Criteria 1 : t > 5 (P-value < 4.3 , LOD > 5.3) : 142 expression phenotypes have at least one significant regulator.

Criteria 2 : t > 4 (P-value < 3.7 , LOD > 3.4): 984 expression phenotypes have at least one significant regulator.

cis and trans regulation
Cis and trans- regulation

Under criteria 1,

  • 27/142 (19%) expression phenotype have only a single cis-regulator.
  • 110/142 (77.5%) expression phenotype have only a single trans-regulator.
  • 2 /142 have a cis and a trans-acting regulator
  • 3 /142 gene expression have two trans-acting regulator

Under criteria 2,

164 / 984 (16%) has multiple regulators

slide14

5 Mb window (total 491 windows)

T-statistic

1

2

3

.

.

.

3554

Gene expression “Target”

Criteria 2

t > 3.4

SNP 1 2 3 …..2756

SNP 1 2 3 …..2756

Genetic Locus “regulator”

master regulator
Master regulator

31 25

14q32 20q13

Divide the autosomal genome into 491 windows of 5 Mb, and count the number of regulators in the regions under criteria 2 (total 984 phenotypes with significant linkages).

co regulation
Co-regulation
  • Use the gene expression levels of 94 CEPH grandparents
  • Hierarchical clustering was performed and group genes by the correlation of the 31 target gene expression levels
  • Permutation test was used to determine the significant level of pair-wise correlation.
discussion
Discussion
  • The study applied genome-wide mapping method to identify the chromosomal regions regulate to the gene expression phenotypes.
  • This type of study has the potential to uncover complicated transcriptional control.
  • Cis-, trans-acting and master regulators were discovered.
  • The linkage results are reliable as verified by association study and qRT-PCR.
comments
Comments
  • In this study, gene expression measured in immortalized B cells may be very different from the expression of human B cells in the blood.
  • Co-regulated genes and the pathways that connect genes are identified.
  • We would be even more interested in utilizing the data to improve our understanding of human disease.

Genotype Gene expression Phenotype

slide22
Candidate regions have cis-effects.
  • Different phenotype / expression signatures associated with different “regulators”.
statistical design and analysis issues
Statistical design and analysis issues

Design:

  • Choice of relative type or pedigree in humans.
  • Choice of tissue and timing of mRNA sampling.

Analysis:

  • Multiple testing: linkage location, transcripts.
  • Regulatory hotspots: methods to find master regulatory loci.
  • Regulatory networks: searching for small sets of

Co-regulated transcripts.

reference
Reference
  • Genetic analysis of genome-wide variation in human gene expression. Moley M., Molony C.M, Teresa M. Weber T.M. et al. Nature 430:743-747 (2004).
  • Genetics of gene expression surveyed in maize, mouse, and man. Schadt E.E., Monks S.A., Drake T.A. et al. Nature 422: 297-302 (2003).
  • Mapping expression in randomized rodent genomes. Broman K.W. Nature Genetics 37: 209-210 (2005).
  • Natural variation in human gene expression assessed in lymphoblastoid cells. Cheung V.G., Conlin L.K., Weber T.M. et al. Nature Genetics 33: 422-425 (2003).
  • Mapping determinants of human gene expression by regional and genome-wide association. Cheung V.G., Spielman R.S., Ewens K.G. et al. Nature 437: 1365-1369 (2005).