The evolution of complexity I Iain Mathieson · 2020-01-03 · The evolution of complexity I!! Iain...
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The evolution of complexity I!!
Iain Mathieson!
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There is no theoretical reason to expect evolutionary lineages to increase in complexity with time, and no empirical evidence that they do so. Nevertheless, eukaryotic cells are more complex than prokaryotic ones, animals and plants are more complex than protists, and so on. This increase in complexity may have been achieved as a result of a series of major evolutionary transitions. These involved changes in the way information is stored and transmitted. -‐ SZATHMÁRY & MAYNARD SMITH. Nature. 1994
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Complexity as progress:!
Kuroda et al.; The Lancet; 2001 h1p://en.wikipedia.org/wiki/File:Diagram_of_eye_evoluAon.svg
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Complexity as a random walk:!
Time
Complexity Complexity Complexity Complexity
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(Irreducible) Complexity as a ratchet:!
Ohno; Evolu/on by gene duplica/on; 1970 Force et al. Gene/cs; 1999 Finnegan et al. Nature 2012
Example: gene duplicaAon
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I: Genomic complexity
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Human genome size: ~ 3.2 Gbases ~ 760 Mbytes
Diffs, ~ 1/100 – 1/1000 bases
Human species ~ 5-50 Pbytes
~15 Pb/year
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Composi)on of the human genome “Junk” (64%) 44% transposable elements 9% viral DNA 9% intronic sequence (not included above) 1% pseudogenes “Useful” (9%) 2% protein coding sequence (~20,000 genes) 2% regulatory RNA 2% centromeres 1% essential regulatory regions 2% other conserved regions The rest: ~ 26% unknown but unconserved Source: Laurence Moran Other esAmates of “Useful content” ~3-‐15%
See PonAng & Hardisson Genome Research 2011
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Necturus maculosus 50 Gb
Polychaos Dubium “670Gb”
Fugu rubripes 0.4Gb
Mammals ~3Gb
Lilium longiflorum 90Gb
Archilochus alexandri 0.9Gb
Images: Wikipedia
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h1p://commons.wikimedia.org/wiki/File:Genome_size_vs_number_of_genes.svg
Genome size (Mb)
Num
ber o
f protein cod
ing gene
s
Viruses
Prokaryotes
Eukaryotes
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Abdollahi et al. PNAS 2007
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Genome size Number of genes Mean exonic length/kb Mean intronic length/kb Mean regulatory/kb
3 Gb 24,000 1.3 32 2.0
137 Mb 16,000 1.7 2.9 1.4
100Mb 21,000 1.3 0.64 0.43
12 Mb 6,200 1.44 0.02 0.11
Data: Lynch; The evolu/on of genome architecture; Chapter 3
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transcripAon
splicing
DNA
RNA
RNA
translaAon
Protein
Protein folding
introns exons
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transcripAon
splicing
DNA
RNA
RNA
translaAon
Protein
Protein folding
introns exons
alternaAve splicing
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AlternaAve splicing increases complexity, but is it adapAve?
- Cost of additional transcription. - Damaging splicing errors. - Larger target for damaging mutations.
Figure: Lynch; The evolu/on of genome architecture; Chapter 9
An argument from populaAon geneAcs….
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II: OrganizaAonal complexity
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“The major transiAons” – Maynard Smith and Szathmáry
1. Molecules è Populations of molecules
2. Genes è Chromosomes 3. RNA è DNA 4. Prokaryotes è Eukaryotes 5. Asexual è Sexual 6. Protists è Plants, animals and Fungi 7. Individuals è Colonies 8. Primate societies è Human societies
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Prokaryote Eukaryote
The evoluAon of eukaryotes
Wall
Circular chromosome
Nucleus
Linear chromosomes
Cystoskeleton Mitochondria
Membrane
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Timmins et al. Nature reviews gene/cs. 2004
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The evoluAon of sex and stuff
Asex
FacultaAve sex
Obligate sex
?
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Many explanaAons…
Muller’s ratchet
ConstrucAng advantageous alleles
DNA repair
“Adaptability”
Selfish DNA elements
Chromosome disjuncAon
VariaAon among siblings
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Single cells Colonies Specialization
biofilms
Volvox
The evoluAon of mulAcellularity
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Nature EducaAon 2010
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EvoluAon of social behavior
h1p://en.wikipedia.org/wiki/File:Wasp_a1ack.jpg
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Kin selecAon
Haldane: Lay down my life to save my brother? “No, but I would to save two brothers or eight cousins.”
Hamilton’s rule: rB > C
Dawkins: “The selfish gene”
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Ecosystems Species Social Groups Individuals Cells Genes
Higher levels
Example: Nowak et al. Nature; 2010
MulA-‐level selecAon
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Control mechansims
- Mitochondrial gene loss - Tumor suppressor genes - Imprinting - Social punishment
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GeneAc drip
Remember, weakly deleterious alleles will still fix with p ~ 1/2Ne
Li & Durbin; 2011
h1p://evoluAon.berkeley.edu/
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Insights from biological complexity: - Rare, large and important jumps in qualitative complexity - Complexity may increase when selection is relaxed –it’s not necessarily directly adaptive.
- The mechanisms by which complexity is increased may not be the same ones which maintain it.
- Contingency is important. Eukaryotes only evolved once.
QuesAons about biological complexity: - How should we measure the complexity of features, organisms and environments?
- How hard is it to drift across “fitness valleys”?
- Can we tell when a feature is adaptive?
- What’s the relative role of different selective mechanisms in the evolution of different features?