Genome Evolution. Amos Tanay 2009 Genome evolution Lecture 10: Comparative genomics, non coding sequences

Genome Evolution. Amos Tanay 2009

Genome evolution

Lecture 10: Comparative genomics, non coding sequences


Why larger genomes?

• Ameobe dubia – 670Gb! • S. cerevisae is 0.3% of human, D. melanogaster is 3%• Selflish DNA –

– larger genomes are a result of the proliferation of selfish DNA– Proliferation stops only when it is becoming too deleterious

• Bulk DNA– Genome content is a consequence of natural selection– Larger genome is needed to allow larger cell size, larger nuclear membrane etc.


Why smaller genomes?

• Metabolic cost: maybe cells lose excess DNA for energetic efficiency– But DNA is only 2-5% of the dry mass– No genome size – replication time correlation in prokaryotes– Replication is much faster than transcription (10-20 times in E. coli)


Mutational balance• Balance between deletions and insertions

– May be different between species– Different balances may have been evolved

• In flies, yeast laboratory evolution– 4-fold more 4kb spontaneous insertions

• In mammals – More small deletions than insertions

Mutational hazard• No loss of function for inert DNA

– But is it truly not functional?

• Gain of function mutations are still possible:– Transcription– Regulation

Differences in population size may make DNA purging more effective for prokaryotes, small eukaryotesDifferences in regulatory sophistication may make DNA mutational hazard less of a problem for metazoan


Repeats: selfish DNA


Retrotransposition via RNA

ClassCopiesGenome Fraction

LINEs868,000(only ~100 active!!)

20.4%

SINEs1,558,000

(70% Alu)

13.1%

LTR elements

443,0008.3%

Transposons294,0002.8%

Repetitive elements in the human genome


Burst of repeats activity

Han et al. 2005


Age of repeats in the human genome


DNA and gene distribution in the isochore families of the human genome

Bernardi G. PNAS 2007;104:8385-8390

These trends are quite clear. But the existence of distinct isochore classes can be questioned


Bernardi G. PNAS 2007;104:8385-8390

The selection hypotheses on the origin of G+C content heterogeneity


Genomic information: Protein coding genes


Genome information: RNA genesmRNA – messenger RNA. Mature gene transcripts after introns have been processed out of the mRNA precursor

miRNA – micro-RNA. 20-30bp in length, processed from transcribed “hair-pin” precursors RNAs. Regulate gene expression by binding nearly perfect matches in the 3’ UTR of transcripts

siRNA – small interfering RNAs. 20-30bp in length, processed from double stranded RNA by the RNAi machinary. Used for posttranscriptional silencing

rRNA – ribosomal RNA, part of the ribosome machine (with proteins)

snRNA – small nuclear RNAs. Heterogeneous set with function confined to the nucleus. Including RNAs involved in the Splicesome machinery.

snoRNA – small nucleolar RNA. Involved in the chemical modifications made in the construction of ribosomes. Often encode within the introns of ribosomal proteins genes

tRNA – transfer RNA. Delivering amino-acid to the ribosome.

piRNA – silencing repeats in the germline


Gene content in the genome

M. Lynch


Genome information: Introns/Exons


Pseudogenes

Genes that are becoming inactive due to mutations are called pseudogenes

mRNAs that jump back into the genome are called processed pseudogenes (they therefore lack introns)

M. Lynch


Adaptive evolution of non-coding DNA in Drosophila(P. Andolfatto, 2005)

12 D. melanogaster collected in Zimbabwe 188 regions of ~800bp, surveyed for polymorphisms compared to sequences of D. simulans to measure divergenceClassified loci according to genomic context


Estimating

Theorem: Let u be the mutation rate for a locus under consideration, and set =4Nu. Under the infinite sites model, the expected number of segregating sites is:

1

1

1)(

n

i iSE

1

1

1/

n

iW i

S

The Waterston estimator for theta is:

Definition: Let ij count the number of differences between two sequences. The average number of pairwise difference in a sample of n individuals is:

jiijn

n

,

1

2

Theorem: as always, =4Nu. We have:

nE


Tajima’s D

Theorem: as always, =4Nu. We have:

nE

Proof:

)1/(1)41/(1 Nu

Going backwards. Coalescent is occuring before mutation in a rate of:

1

1

1)( 2

k

kP

After one mutation occurred, we again have the same rate so overall:

The expected value of this geometric series is and so is the average of all pairs.

Definition: Tajima’s D is the difference between two estimators of :

WD


Tajima’s D for classes of drosophila sequence

Definition: Tajima’s D is the difference between two estimators of :

WD

High D values: allele multiplicities are spread more evenly than expected – (why?)

Low D values: More rare alleles are present (Why?)


Adaptive evolution of non-coding DNA in Drosophila(P. Andolfatto)

The proportion of divergence driven by positive selection:

= 1–(DSPX/DXPS)


Phastcons (A. Siepel)

Siepel A. et.al. Genome Res. 2005;15:1034-1050

Each model is context-less

Transition parameters are kept fixed – this determine the fraction of conserved sequence

Inference on the phyloHMM -> inferred conserved model posteriors

Use threshold to detect contiguous regions of high conservation posterior

Learning the branch lengths


Siepel A. et.al. Genome Res. 2005;15:1034-1050

Phastcons parameters


Fixation probabilities and population size: what selection coefficient can drive a 70% decrease in substitution rate (if N_e = 10,000)?

NsNs

Nsp

NNp e

s

e

eTTP

44

4

022 1

2

1

1)(

-0.005

0

0.005

0.01

0.015

0.02

-0.005 -0.003 -0.001 0.001 0.003 0.005 0.007 0.009

Ne=100

Ne=1000

Ne=10000

Ne=100000

1E-40

1E-38

1E-36

1E-34

1E-32

1E-30

1E-28

1E-26

1E-24

1E-22

1E-20

1E-18

1E-16

1E-14

1E-12

1E-10

0.00000001

0.000001

0.0001

0.01

-0.005 -0.003 -0.001 0.001 0.003 0.005 0.007 0.009

Ne=100

Ne=1000

Ne=10000

Ne=100000


ENCODE


481 segment longer than 200bp that are absolutely conserved between human, mouse and rat (Bejerano et al 2005)

What are these elements doing? Why they are completely conserved? 4 Knockouts are not revealing significant phenotypes..

Ahituv et al. PloS Biolg 2007

Ultra-conserved elements


Katzman et al., Science 2007

Population genetics do suggest ultraconserved elements are under selection

Separating mutational effects from selective effect is still a challenge…

Ultra-conserved elements

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Genome Evolution. Amos Tanay 2009 Genome evolution Lecture 10: Comparative genomics, non coding sequences