Comparative Genomics II:Functional comparisons

Caterino and Hayes, 2007

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

Functional variation within and among species

Human

Chimp

Rhesus

Mouse

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

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

Neutral Constrained Directional

Patterns of selection on gene expression and regulation

Romero et al., Nat Rev Genet. 13:505 (2012)

Comparative approaches to identify conserved andvariant regulatory functions

Visel and Pennacchio, Nat Genet 42:557 (2010)

Regulatory conservation

Regulatory rewiring

Furey and Sethupathy, Science 2013

Genetic drivers of gene regulatory variation

• 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 inChIP-seq signals

•Input data are noisy: ChIP-seq, RNA-seq data are signal based, subjectto 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

•10 human lymphoblastoid cell lines3 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

NFkB

PolI

IPair

wis

e d

iffere

nce

in

bin

din

g

Fra

cti

on

of

reg

ion

sb

ou

nd

# individuals

Variation in TF binding is common

Science 342: 747 (2013)

•10 human lymphoblastoid cell lines1 population group (Nigerian)

All analyzed by HapMap and 1000 Genomes

•Targets:

RNA Polymerase II

H3K4me1, H3K4me3, H3K27ac, H3K27me3

DNase hypersensitivity

Measuring allelic imbalance in histone modification profiles

G allele

T allele

Need to map reads reliably to individual alleles

ChIP-seq reads

Allelicimbalance

Cis-quantitative trait loci

~1200 identified

Science 328: 1036 (2010)

•Targets:

CCAAT/enhancer binding protein a (CEBPA)

Hepatocyte nuclear factor 4a (HNF4A)

Essential for normal liver development and function

•Tissue:

Adult liver from 4 mammal species plus chicken

Lineage-specific gain and loss of CEBPA binding in liver

Lineage-specific: 0 bp overlap in multiple species alignment

Widespread variation in CEBPA binding in mammals

Widespread variation in CEBPA binding in mammals

Cell 154: 530 (2013)

Enhancer-associatedhistone modification

Single TF binding events may not indicate regulatory function

• Many TFs are present at high concentrationsin the nucleus

• TF motifs are abundant in the genome

• Single TF binding events may be incidental

Combinatorial TF binding events are more conserved

Many TF binding changes do not have obvious genetic causes

In mammalian liver:

Many TF binding changes do not have obvious genetic causes

In mouse liver:

Human

Rhesus

Mouse

Bud stage; digitspecification Digit separation

Cell 154: 185 (2013)

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

Mapping active promoters and enhancers in human limb

ENCODE cell lines

H3K27ac

Gains in promoter and enhancer activity

• Bone morphogenesis• Chondrogenesis• Digit malformations in mouse

Human-specific H3K27ac marking correlates with changes inenhancer function

Epigenetic signatures reflect tissue identity and species relationships

H3K27ac signal in human and mouse

Primate

Mouse

H3K27ac in human, rhesus, mouse

• 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)

Global patterns of gene expression differences

Gene expression recapitulates species phylogenies

Gene expression divergence rates are tissue-specific

liver

testis

brain

Gene expression divergence increases with evolutionary time

Conservation of core organ functions restricts divergence

•Comparative functional genomics identifies regulatory differenceswithin and among species

•TF binding is variable within species and highly variable among species

•Epigenetic comparisons provide more insight into biologicallyrelevant regulatory diversity and divergence

•Gene regulation and expression diverges with increasingphylogenetic distance – they mirror neutral expectation

Summary