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

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

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

  2. Outline • Introduction • Data • Method: Linkage analysis • Results • Discussion • Comments

  3. Introduction

  4. Goal : Identify loci associated with variation in expression levels Nucleus regulators Genomic DNA mRNA mRNA Target

  5. Trans-regulator Cis-regulator Cis and Trans regulation Target gene expression phenotype

  6. 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)

  7. 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.

  8. 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.

  9. 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

  10. 15 10 5 For a particular target gene expression t-statistics SNP1 2 3 4 5 Genetic Locus

  11. 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.

  12. 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

  13. 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”

  14. 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).

  15. 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.

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  17. Population-based association analysis for cis-regulators (SNP regulator)

  18. 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.

  19. 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

  20. Candidate regions have cis-effects. • Different phenotype / expression signatures associated with different “regulators”.

  21. 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.

  22. 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).

  23. Question?

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