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Comparative Genomics II: Functional comparisons Caterino and Hayes, 2007.

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Presentation on theme: "Comparative Genomics II: Functional comparisons Caterino and Hayes, 2007."— Presentation transcript:

1 Comparative Genomics II: Functional comparisons Caterino and Hayes, 2007

2 Overview I. Comparing genome sequences Concepts and terminology Methods  Whole-genome alignments  Quantifying evolutionary conservation (PhastCons, PhyloP, GERP)  Identifying conserved elements Utility and limitations of conservation Available datasets at UCSC II. Comparative analyses of function Evolutionary dynamics of gene regulation Case studies Insights into regulatory variation within and across species

3 Functional variation within and among species Human Chim p Rhes us Mous e

4 Modularity of developmental gene expression forebrain gene A Brain TFs neural tube gene A Neural TFs limb Limb TFs gene A Regulatory changes introduce variance without disrupting protein function Regulatory variation contributes to human phenotypic variation overall

5 Lettice et al. Hum Mol Genet 12:1725 (2003) Sagai et al. Development 132:797 (2005) Regulatory mutations affecting pleiotropic genes cause discrete developmental changes

6 NeutralConstrainedDirectional Patterns of selection on gene expression and regulation Romero et al., Nat Rev Genet. 13:505 (2012)

7 Comparative approaches to identify conserved and variant regulatory functions Visel and Pennacchio, Nat Genet 42:557 (2010) Regulatory conservation Regulatory rewiring

8 Furey and Sethupathy, Science 2013 Genetic drivers of gene regulatory variation

9 H3K4me2 H3K27ac H3K4me2 H3K27ac Comparative analysis of ChIP-seq datasets Human Mouse Compare TF binding, histone modifications, DNase hypersensitivity in equivalent tissues Requires a statistical framework to reliably quantify changes in ChIP-seq signals

10 Input data are noisy: ChIP-seq, RNA-seq data are signal based, subject to considerable experimental variation Using comparable biological states within and across species (e.g., human liver vs. mouse liver) = variation across tissues? How do epigenetic states and gene expression diverge among individuals and across species (Neutral? Constrained?) Can we identify variants or substitutions that drive regulatory changes? Issues in comparative functional genomics

11 10 human lymphoblastoid cell lines 3 major population groups: European, East Asian, Nigerian 9 females, 1 male 9 analyzed by HapMap and 1000 Genomes Science 328: 232 (2010) Targets: RNA Polymerase II NFkB

12 PolII Pairwise difference in binding Fraction of regions bound # individuals Variation in TF binding is common

13 Science 342: 747 (2013) 10 human lymphoblastoid cell lines 1 population group ( Nigerian) All analyzed by HapMap and 1000 Genomes Targets: RNA Polymerase II H3K4me1, H3K4me3, H3K27ac, H3K27me3 DNase hypersensitivity

14 Measuring allelic imbalance in histone modification profiles G allele T allele Need to map reads reliably to individual alleles ChIP-seq reads Allelic imbalance

15 Cis-quantitative trait loci ~1200 identified

16 Science 328: 1036 (2010) Targets: CCAAT/enhancer binding protein  (CEBPA) Hepatocyte nuclear factor 4  (HNF4A) Essential for normal liver development and function Tissue: Adult liver from 4 mammal species plus chicken

17 Lineage-specific gain and loss of CEBPA binding in liver Lineage-specific: 0 bp overlap in multiple species alignment

18 Widespread variation in CEBPA binding in mammals

19

20 Cell 154: 530 (2013)

21 Enhancer-associated histone modification Single TF binding events may not indicate regulatory function Many TFs are present at high concentrations in the nucleus TF motifs are abundant in the genome Single TF binding events may be incidental

22 Combinatorial TF binding events are more conserved

23 Many TF binding changes do not have obvious genetic causes In mammalian liver:

24 Many TF binding changes do not have obvious genetic causes In mouse liver:

25 Human Rhesus Mouse Bud stage; digit specification Digit separation Cell 154: 185 (2013)

26 Identifying human-lineage changes in promoter and enhancer function Compare H3K27ac signal at orthologous sites ‘Stable marking’: 1.5-fold or less change in H3K27ac among human, rhesus and mouse Human gain: require significant, reproducible gain in human versus all 12 datasets in rhesus and mouse

27 Mapping active promoters and enhancers in human limb ENCODE cell lines H3K27ac

28 Gains in promoter and enhancer activity Bone morphogenesis Chondrogenesis Digit malformations in mouse

29 Human-specific H3K27ac marking correlates with changes in enhancer function

30 Epigenetic signatures reflect tissue identity and species relationships H3K27ac signal in human and mouse Primate Mouse H3K27ac in human, rhesus, mouse

31 Human Chimpanzee Bonobo Gorilla Orangutan Macaque Mouse Opossum Platypus Chicken Custom gene models based on Ensembl + RNA-seq 5,636 1:1 orthologs in amniotes 13,277 1:1 orthologs in primates Only constitutive exons Nature 478: 343 (2011)

32 Global patterns of gene expression differences

33 Gene expression recapitulates species phylogenies

34 Gene expression divergence rates are tissue-specific liver testis brain

35 Gene expression divergence increases with evolutionary time Conservation of core organ functions restricts divergence

36 Comparative functional genomics identifies regulatory differences within and among species TF binding is variable within species and highly variable among species Epigenetic comparisons provide more insight into biologically relevant regulatory diversity and divergence Gene regulation and expression diverges with increasing phylogenetic distance – they mirror neutral expectation Summary


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