Genetic variation and RNA-seq

Transcription

1 Power of RNA-seq; Course Genetic variation and RNA-seq Applications of RNA-seq in Genetical Genomics Laboratory of Nematology; Kammenga lab L. Basten Snoek

2 Research topics C. elegans Genetics What How Arabidopsis Natural variation Gene expression Lifespan Development Environment Stress resistance Adaptation G x E Genetical genomics QTL mapping DNA- and RNA-seq Micro-arrays Image analysis Network/Systems biology High-throughput phenotyping

3 Genetical genomics Gene expression variation linked to genetic polymorphisms expression Quantitative Trait Locus (eqtl). Gene expression

4 expression QTL How do we find an eqtl? Quantitative Trait Locus Genetic variation Alleles Gene X Allele 1: ~CATGGACTG~ Allele 2: ~CATGAACTG~ Different combinations of alleles Gene X1 :: Gene Y1 :: Gene Z1 Gene X2 :: Gene Y2 :: Gene Z2 Gene X1 :: Gene Y2 :: Gene Z1 Gene X2 :: Gene Y1 :: Gene Z2 Gene X1 :: Gene Y2 :: Gene Z2 Gene X1 :: Gene Y1 :: Gene Z2 Gene X2 :: Gene Y2 :: Gene Z1 Gene X2 :: Gene Y1 :: Gene Z1

5 expression QTL How do we find an eqtl? Obtain a mapping population Quantitative Trait Locus

6 expression QTL How do we find an eqtl? Measure a phenotype Quantitative Trait Locus

7 expression QTL High Quantitative Trait Locus How do we find an eqtl? Low Search for a link between a genetic locus and the phenotypic distribution

8 expression QTL Quantitative Trait Locus How do we find an eqtl? Use a statistical test to test for a significant linkage. Identify eqtl!

9 expression QTL What does this eqtl tell us? Quantitative Trait Locus A polymorphism affecting the variation in gene expression can be found at this locus Gene Genetic variation Polymorphic regulator Gene expression variation QTL

10 expression QTLs What do these eqtls tell us? Quantitative Trait Locus Genome wide scan of polymorphic regulators Essential info per gene: Position - Genomic - eqtl peak(s)

11 expression QTLs Quantitative Trait Locus What do these eqtls tell us? Genome wide scan of polymorphic regulators Co-regulated genes Polymorphic Regulator eqtls Regulation Targets

12 expression QTLs Quantitative Trait Locus What do these eqtls tell us? Genome wide scan of polymorphic regulators Co-regulated genes Phenotypic variation Polymorphic Regulator eqtls Regulation Targets

13 expression QTLs in context What do these eqtls tell us? Genome wide scan of polymorphic regulators Co-regulated genes Context dependent regulators Juvenile Reproducing Old Quantitative Trait Locus Viñuela & Snoek etal 2010

14 Snoek, Elvin, Rodriquez etal, in prep; Snoek & Sterken etal, in prep expression QTLs in context What do these eqtls tell us? Genome wide scan of polymorphic regulators Co-regulated genes Context dependent regulators Quantitative Trait Locus Environmental variation Phenotypic variation Polymorphic Regulator eqtls Regulation Targets

15 Requirements for eqtl detection Mapping population Crossing two genetically different individuals Genetic markers, polymorphisms, SNPs PCR, FLP, AFLP, Micro-satellites Transcript level variation Micro-arrays RNA-seq eqtls Phenotypic variation Polymorphic Regulator Regulation Targets

16 RNA-seq and genetic variation Mapping population Crossing two genetically different individuals CB4856, Hawaii 1 SNP per ~800 bp N2, Bristol RNA-seq RNA-seq

17 RNA-seq and genetic variation Gene expression differences

18 RNA-seq and genetic variation Example: pgp-6, genotype specific transcript levels Viñuela & Snoek etal 2010

19 RNA-seq and genetic variation Example: pgp-6, new exons Li, Breitling, Snoek, van der Velde, Swertz, Riksen, Jansen & Kammenga, 2010, Genetics

20 RNA-seq and genetic variation Example: F08A8.2, variation in exon usage

21 average coverage RNA-seq and genetic variation Example: F08A8.2, variation in exon usage F08A8.2 N2 CB exon

22 Mapping population Genetic variation Crossing two genetically different individuals CB4856, Hawaii Phenotypic variation Polymorphic Regulator N2, Bristol eqtls Regulation Targets Li & Alvarez etal. 2006; Doroszuk etal 2009; Reddy & Andersen etal 2009; McGrath etal 2009; Rockman etal 2010; Viñuela & Snoek etal 2010; Elvin & Snoek etal 2011; Viñuela & Snoek etal 2012; Rodriguez etal 2012; Green etal 2013 Snoek etal 2013

23 RNA-seq, two for the price of one Information from RNA-seq Gene expression Transcript level variation Polymorphisms Genetic markers In the same experiment! Phenotypic variation Polymorphic Regulator Individuals/Lines Different: Genotypes, Phenotypes Mapping population RNA-seq Per Genotype: I) Gene expression II) Polymorphisms Genetic variation Gene expression variation eqtls Regulation Targets eqtls Regulators Targets

24 Data Storage, Raw, Processed Raw data-points

25 Data Storage, Raw, Processed Data points, accessibility, visualization Raw data-points Processed data-points

26 RNA-seq vs Micro-arrays RNA-seq Micro-arrays Price ~200 (10M reads) <100 (44K spots) Genetic variation Gene expression Splice variants New genes ++ - Sample preparation + + Feature extract time PC power Cluster Desktop Non model species

27 Summary RNA-seq is useful for: Non-model species New mapping populations Linking gene expression variation to genetic variation Measuring splicing Micro-arrays are useful for experiments needing many measurements (on model species) Example: time-series on populations

28 Acknowledgements Wageningen - Kammenga lab - Harm Nijveen Kiel - Schulenburg lab Gent - Braeckman lab Groningen - Jansen lab - Swertz lab Cambridge - Fisher lab - Babu Lab Manchester - Poulin lab Liverpool - Cossins lab Paris - Nechaev lab Zurich - Hajnal lab - Hengartner lab Barcelona - Lehner lab