Rosalind Elsie Franklin Biophysicist and

crystallographer X-ray diffraction

images of DNA Tobacco mosaic

and polio viruses 1920-1958

(source: wikipedia)

A Structural Split in the Human Genome

Clara S. M. Tang and Richard J. EpsteinPLoS One (2007) 7:e603

February 13, 2007I. Elizabeth Cha

Introduction

PCIsPromoter-associated CpG islands

Mediate methylation-dependent gene silencing

Co-locate to transcriptionally active genes

60% of human genes contains PCIs

CpG Islands

Genomic regions containing high frequency of CG dinucleotides

CpGcytidine-phosphodiester-guanosine

Formal definition At least 200bp GC percentage >50% CpG ratio >60%

DNA Methylation

Materials and Methods Sequence data and annotations Determination of CpG island overlapping

transcription start site Housekeeping genes and paralogs of

pseudogenes Bimodal distribution of GC content Gene expression data Evolutionary rate determination Principal component analysis

Sequence Data and Annotations

UCSC genomic assemblies, RefSeq dataset, Emsembl gene dataset Human (hg18, 3/2006) Mouse (mm6, 3/2006) Fugu (fr1, 8/2002) Fruit fly (dm2, 4/2004) Worm (ce2, 3/2004)

Data Preprocessing

RepeatMask – Alu Discard sequences

Not commencing with ATG codons Not terminating with canonical stop

codons

Retain the longest genomic sequences containing identical exonic sequences

Determination of CpG Island Overlapping Transcription Start Site

Download CpG islands annotation (cpgIslandExt) from UCSC

Identify CpG islands overlapping with promoter regions

Map with RefGene annotation (200bp upstream and 500bp downstream)

Data and Tools

502 Housekeeping genes 1220 pseudogene paralogs

NOCOM program SAGEmap Homologue data XSTAT

Results – PCI+ Genes

Housekeeping genehigher GC contentlower intron length/number

Pseudogene paraloglower GC contenthigher intron length/number

Functional distinguishable

Table 1

Results – PCI- Genes

Higher evolutionary rate Narrower expression breadth than

PCI+ genes More frequent tissue-specific

inactivation

Figure 1 Biphasic GC/AT Distribution of PCI+ Genes

A. Distribution of GC content among different regions of genes

3’ UTR

5’ UTR

coding region

intronic

Figure 1 Biphasic GC/AT Distribution of PCI+ Genes (cont’d)

With ‘start’ CpG islands (CGI+)

Without ‘start’ CpG islands (CGI+)

B&C Proportion of genes among different GC groups.

Figure 2 GC Content of Promoter vs. Non-promoter CpG Island Overlapping Genes

All genesGenes with medium total intron size (10-50kb)

Intronless genes

Genes with short total intron size (<10kb) and long intron size (>50kb)

PCI+: solid line; PCI-: dash line

Figure 3 Distribution of Coding GC% of RefGenes with PCIs

pseudogenes House-keeping genes

Figure 4 Quantitative Comparison of Gene Subsets

L: low, GC<40%; H: high, GC>65%;

double dark, <0.001; single dark, <0.01; open, < 0.05

Figure 4 Quantitative Comparison of Gene Subsets (cont’d)

L: low, GC<40%; H: high, GC>65%;

double dark, <0.001; single dark, <0.01; open, < 0.05

Figure 4 Quantitative Comparison of Gene Subsets (cont’d)

L: low, GC<40%; H: high, GC>65%;

double dark, <0.001; single dark, <0.01; open, < 0.05

Figure 6 Model of human genomic evolution

Conclusions

PCIs Transcriptional regulators Evolutionary accelerators to facilitate

intron insertion

Mthylated PCIs on transcription and chromatin accelerate adaptive evolution towards biological complexity

Conclusions Adaptive evolution of human genome

Declining transcription of a subset of PCI+ genes

Predisposing to both CpGTpA mutation and intron insertion

Biological complexity model Environmentally selected gains/losses of

PCI methylation (+/-) Polarizing PCI+ gene structures arounda

genomic core of ancestral PCI- genes

Discussion

AT-rich, PCI+ gene vs. GC-rich PCI+ housekeeping gene Lower transcriptional activity Higher intron number Higher evolutionary rate

Loss of negative selection pressure

Discussion (cont’d)

PCI- genes vs. PCI+ genes Higher evolutionary rate Lower expression breadth

Intron number relates more directly to PCI positivity

Figure 5 Principal component analysis (PCA)

A. PCA analysis using six variables at either 53% (left) or 59% (right) variance

Figure 5 Principal component analysis (PCA) (cont’d)

B. 2D dot plots C. 3D dot plots

GC-rich, blue; GC-poor, red