Understanding the Prokaryotic Contributions to the Eukaryotic Genome: A Network Approach

James McInerneyNUI Maynooth*

http://bioinf.nuim.ie/

Current address:Harvard University (2012-2013)Thursday 11 July 13

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Falsifiability

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Concilience

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Evolutionary analyses of non-genealogical bondsproduced by introgressive descentEric Baptestea,1, Philippe Lopeza, Frdric Bouchardb, Fernando Baqueroc, James O. McInerneyd, and Richard M. BurianeaUnit Mixte de Recherche 7138 Systmatique, Adaptation, Evolution, Universit Pierre et Marie Curie, 75005 Paris, France; bDpartementde Philosophie, Universit de Montral, Montral, QC, Canada H3C 3J7; cDepartment of Microbiology, Ramn y Cajal University Hospital(IRYCIS, CIBERESP), 28034 Madrid, Spain; dMolecular Evolution and Bioinformatics Unit, Department of Biology, National University ofIreland Maynooth, County Kildare, Ireland; and eDepartment of Philosophy, Virginia Tech, Blacksburg, VA 24061

Edited by W. Ford Doolittle, Dalhousie University, Halifax, Canada, and approved September 24, 2012 (received for review April 20, 2012)

All evolutionary biologists are familiar with evolutionary units that evolve by vertical descent in a tree-like fashion in single lineages.However, many other kinds of processes contribute to evolutionary diversity. In vertical descent, the genetic material of a particularevolutionary unit is propagated by replication inside its own lineage. In what we call introgressive descent, the genetic material ofa particular evolutionary unit propagates into different host structures and is replicated within these host structures. Thus, introgressivedescent generates a variety of evolutionary units and leaves recognizable patterns in resemblance networks. We characterize six kinds ofevolutionary units, of which ve involve mosaic lineages generated by introgressive descent. To facilitate detection of these units inresemblance networks, we introduce terminology based on two notions, P3s (subgraphs of three nodes: A, B, and C) and mosaic P3s, andsuggest an apparatus for systematic detection of introgressive descent. Mosaic P3s correspond to a distinct type of evolutionary bond thatis orthogonal to the bonds of kinship and genealogy usually examined by evolutionary biologists. We argue that recognition of theseevolutionary bonds stimulates radical rethinking of key questions in evolutionary biology (e.g., the relations among evolutionary playersin very early phases of evolutionary history, the origin and emergence of novelties, and the production of new lineages). This line ofresearch will expand the study of biological complexity beyond the usual genealogical bonds, revealing additional sources of biodiversity.It provides an important step to a more realistic pluralist treatment of evolutionary complexity.

biodiversity structure | evolutionary transitions | lateral gene transfer | network of life | symbiosis

E volutionary biologists often studythe origins of biodiversity throughthe identication of the unitsat which evolution operates. Inagreement with the work by Lewontin (1),it is commonly assumed that such unitspresent a few necessary conditions forevolution by natural selection, namely (i)phenotypic variation among members ofan evolutionary unit, (ii) a link betweenphenotype, survival, and reproduction(i.e., differential tness), and (iii) herita-bility of tness differences (individualsresemble their relatives more than un-related individuals). This view, however,raises at least two difcult questions.What can be selected? What evolvesby selection?This dual concern has prompted a dis-

tinction (2, 3) between units of selectionand units of evolution, distinguishing be-tween vehicles (or interactors) (4) onwhich selection can act (usually individualsor populations) and replicators (usuallyindividual genes or small complexes ofgenes), the ultimate beneciaries of evo-lution (2, 3). Replicators are consensuallyseen as central to evolutionary expla-nations (5). However, the consensus ismore uid regarding the denition ofinteractors. Debates about levels of selec-tion and the multilevel selection theory(510) have led to investigations ofwhether interactors can be found atdistinct levels of organization (cells, or-ganisms, groups of organisms, and evenfor some, species) when survival of genesis affected by competition on various levels

of organization in ways that may conictacross levels.For instance, some considered that

kin selection among related insects wassufcient to account for the seeminglyhigher level of organization in collectives ofeusocial insects (2, 3, 1113). For others,the colony existed as a selectable whole,irreducible to the simple addition ofindividual insects fates (1417). Thismultilevel perspective seems notably jus-tied if some replicators (genes) arefavored by their phenotype expressed inindividual insects, whereas other genes arefavored because selection acts on theirextended phenotype expressed in the col-lective distributed behavior in groupsof insects.Although evolutionary biologists can

agree that interactions of entities at dif-ferent levels of organization inuencewhich genes that are replicated acrossgenerations, they need to explain howa hierarchy of levels of organization haditself evolved. This question was tackledin the research program on evolutionarytransitions (1821). As many works havenoted (18, 2022), complex interactorscorresponding to a special type of organi-zation did not appear ex nihilo; theyhave evolved from simpler organizationallevels, and evolution itself has shapedhow each of these organizational levelsis maintained.Accordingly, studies of evolutionary

units must address the order, constraints,and processes through which units fromdifferent levels emerged. Distinct cases

were made to explain micro- and majorevolutionary transitions. For instance, itwas proposed that evolution of higher-levelinteractors results from the functionalintegration and suppression of competitionbetween related lower-level interactors,like in scenarios for the fraternal tran-sition from unicellularity to multicellular-ity (23), or from the egalitarianassortments of unrelated entities interact-ing in ways that lead to new entities (23),like in the symbiogenetic account of theeukaryotes in the work by Margulis (24).Although evolutionary scenarios often

focused on transitions affecting memberswithin a single lineage, there is increasingevidence that processes using genetic ma-terial from multiple sources also had majoreffects on the evolution of a diversity ofinteractors. Recombination, lateral genetransfer (also called horizontal genetransfer) (SI Text, section 1), and symbiosiscontribute to the structure of the bi-ological world in ways that differ fromvertical descent alone (25). Novelty-

Author contributions: E.B., F. Bouchard, F. Baquero, andR.M.B. designed research; P.L. performed research; J.O.M.contributed new reagents/analytic tools; E.B. and P.L. ana-lyzed data; and E.B., P.L., F. Bouchard, F. Baquero, J.O.M.,and R.M.B. wrote the paper.

The authors declare no conict of interest.

This article is a PNAS Direct Submission.1To whom correspondence should be addressed. E-mail:eric.bapteste@snv.jussieu.fr.

This article contains supporting information online atwww.pnas.org/lookup/suppl/doi:10.1073/pnas.1206541109/-/DCSupplemental.

www.pnas.org/cgi/doi/10.1073/pnas.1206541109 PNAS Early Edition | 1 of 7

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Link between lethality and informational genes

0

2000

137 316237

1610

Lethal Viable

ArchaebacteriaEubacteria

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55 31257

1483

Info Oper

LethalViable

Informational genes are significantly more likely to be lethal than operational genes (or=2.98; 2.03-4.40).

An archaebacterial homolog is almost 3 times as likely to be lethal upon deletion as a eubacterial homolog (or=2.96; 2.32-3.77).

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Informational genes, or=2.01; 0.92-4.41

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35

1820

39

Lethal Viable

ArchaebacteriaEubacteria

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102 257210

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Lethal Viable

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Lethality of archaebacterial genes is almost identical across the two categories

Operational genes, or=1.89; 1.43-2.

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P-values are bootstrap probabilities for the mean of the statistic in archaebacteria being less than or equal to the mean in eubacteria, based on 10,000 replicates.

Cotton and McInerney, PNAS, 107:40 17252-17255 (2010)Thursday 11 July 13

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The playground.

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EubacterialEubacterialEubacterial ArchaebacterialArchaebacterialArchaebacterial

n Median Average n Median Average P-valuea

Expression level 6735 15.70 89.68 776 17.29 203.62 0.047 *

Expression breadth 6735 12.00 12.68 776 17.00 13.78 0.014 *

dN/dS 6612 0.10 0.13 764 0.09 0.12 0.006 **

Degree 3342 3.00 7.01 489 4.00 8.06 0.003 **

Betweenness 3342 2.07105 4.10104 489 4.03105 3.74104 0.037 *

Closeness 3342 0.22 0.21 489 0.23 0.22 3.42104 ***

Protein length 7884 540.00 707.41 939 496.00 665.19 3.26107 ***

# Paralogs 7884 3.00 4.31 939 1.00 2.86 7.831034 ***

n PercentPercent n PercentPercent P-valuea

Lethal mouse orthologsb 2588 44.3%44.3% 247 52.2%52.2%

A broader selection

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Eukaryote_a

Archaebacteria

Eubacteria

Eukaryote_b

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Eukaryote_a

Archaebacteria

Eubacteria

Eukaryote_b

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- 61 yeast genes directly linked to viral genes in our network- 13 (i.e., 21%) encode proteins that locate to the yeast nucleus. - Yeast genes without viral homologs: 21% encode proteins that are targeted to the

nucleus.

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The eubacterial component is flexible

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Un-baking the cake?

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Eukaryotes... are chimaeric are monophyletic are not ancestral to prokaryotes are not derived from planctomycetes dont seem to have nuclei with a numerically large contribution of proteins

from viruses are still a semi-segregated community of genetic goods have archaebacterial proteins that prefer to play with archaebacterial

proteins. have eubacterial proteins that prefer to play with eubacterial proteins have ESP proteins that prefer to play with ESP proteins have expanding and contracting eubacterial families have a relatively constant archaebacterial component have an archaebacterial component that evolves more slowly, is more

highly-expressed, is more likely to be lethal on deletion, is more central in protein-protein interaction networks.

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Thanks NUI Maynooth:

Chris Creevey, Mary OConnell, Melissa Pentony, David Fitzpatrick,Gayle Philip,Jennifer Commins,Davide Pisani,James Cotton,Simon Travers,Rhoda Kinsella,Fergal Martin,Carla Cummins,Leanne Haggerty,Aoife Doherty,Sinead HamiltonDavid lvarez-Ponce

External Collaborators:Bill Martin, Duesseldorf, GermanyMartin Embley, Newcastle, UKMark Wilkinson, NHM, London, UKPeter Foster, NHM, London, UKEugene Koonin, NIH, USAMichael Galperin, NIH, USAJohn Allen, QMUL, London, UKNick Lane, Univ. Coll. London, UKEric Bapteste, UPMC, Paris, FrancePhilippe Lopez, UPMC, Paris, FranceFord Doolittle, Dalhousie, Nova ScotiaJohn Archibald, Dalhousie, Nova ScotiaBill Hanage, Harvard School of Public Health

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