Mosaic origin of the eukaryotic kinetochore

Tromer, Eelco C.; Hooff, Jolien J. E. van; Kops, Geert J.P.L.; Snel, Berend

doi:10.1073/pnas.1821945116

Cited by 86 publications

(140 citation statements)

References 77 publications

(101 reference statements)

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“…Independent gene loss is not random [5]. In fact, there are countless observations that cooccurring (or co-lossed) proteins tend to interact [1][2][3][4]39]. This creates an additional opportunity for evaluating orthology methods, namely how well different methods can predict co-occurrence of interacting proteins.…”

Section: Co-occurrence Of Interacting Proteins Is Predicted Similarlymentioning

confidence: 99%

“…Gaining insight into the evolution of eukaryotic pathways and protein complexes is often obtained by careful and intensive manual efforts of inferring orthologous groups (OGs), often using phylogenetic profiles [1][2][3][4]. The reconstructions of the evolution of these pathways is changing our view of eukaryotic genome evolution.…”

Section: Introductionmentioning

confidence: 99%

“…The reconstructions of the evolution of these pathways is changing our view of eukaryotic genome evolution. With the increase of genomic data, specifically of divergent eukaryotes, the pervasiveness of gene loss became a clear pattern for genetic variation [5][6][7] that has been observed in many eukaryotic functional pathways, protein complexes and metabolic pathways [1][2][3][4]8,9]. From these manual reconstructions it is becoming more apparent that the loss of parts of these complexes or pathways between the Last Eukaryotic Common Ancestor (LECA) and extant species is mostly non-random, as whole (sub)complexes are often co-lost or, at least, co-absent.…”

Section: Introductionmentioning

confidence: 99%

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Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution

Deutekom

Snel

Dam

2020

Preprint

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Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets, or expanding the analyses to larger scales. Automated orthology inference should allow such large scale analyses, but substantial differences between orthologous groups generated by different approaches are observed.We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regards to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the Last Eukaryotic Common Ancestor's gene content, pervasiveness of gene loss, and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other.We find that most orthology methods reconstruct a large Last Eukaryotic Common Ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementationThe data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies. Summary •We compared multiple orthology inference methods by looking at how well they perform in recapitulating multiple observations made in eukaryotic genome evolution.• Co-occurrence of proteins is predicted fairly well by most methods and all show similar behaviour when looking at loss numbers and dynamics.• All the methods show imperfect overlap when compared to manually curated orthologous groups and when compared to orthologous groups of the other methods. •Differences are compared between methods by looking at how the inferred orthologies represent a high-quality set of manually curated orthologous groups. •We conclude that all methods behave similar when describing general patterns in eukaryotic genome evolution. However, there are large differences within the orthologies themselves, arising from how a method can differentiate between distant homology, recent duplications, or classifying orthologous groups.

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Section: Co-occurrence Of Interacting Proteins Is Predicted Similarlymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution

Deutekom

Snel

Dam

2020

Preprint

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“…Eukaryotes, on the other hand, exhibit ample evidence of duplication-driven evolution Lynch and Conery (2003) . A prominent example is the kinetochore, which is a large, multi-protein structure in eukaryotes that is essential for cell division, and which formed through extensive gene duplications Tromer et al (2019) . The homologous proteins that arise from gene duplication have been shown to vary considerably in terms of robustness against negative mutations and evolvability towards positive ones Diss et al (2017) ; Dandage and Landry (2019) .…”

Section: Introductionmentioning

confidence: 99%

Duplication accelerates the evolution of structural complexity in protein quaternary structure

Leonard

Ahnert

2020

Preprint

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9Gene duplication, from single genes to whole genomes, has been observed in organisms across all 10 taxa. Despite its prevalence, the evolutionary benefits of this mechanism are the subject of ongoing 11 debate. Gene duplication can significantly alter the self-assembly of protein quaternary structures, 12 impacting the dosage or interaction proclivity. Here we use a lattice model of self-assembly as a 13 coarse-grained representation of protein complex assembly, and show that it can be used to 14 examine potential evolutionary advantages of duplication. Duplication provides a unique 15 mechanism for increasing the evolvability of protein complexes by enabling the transformation of 16 symmetric homomeric interactions into heteromeric ones. This transformation is extensively 17 observed in in silico evolutionary simulations of the lattice model, with duplication events 18 significantly accelerating the rate at which structural complexity increases. These coarse-grained 19 simulation results are corroborated with a large-scale analysis of complexes from the Protein Data 20 Bank. 21 22 37ing. Importantly, both symmetric homomeric and heteromeric interactions are possible, as well 38 as combinations thereof, allowing for more general assembly dynamics than previously permitted 39 in polyomino models. We additionally allow variable genetic length, with genotypes growing and 40 1 of 16 Manuscript submitted to eLife shrinking dynamically through duplication and deletion respectively. 41 The importance of duplication in the structural evolution of proteins was unknown when first 42 encountered in the 1970s, but was quickly realised to be ubiquitous McLachlan (1979). Whether 43 duplication is predominantly a driver of innovationMagadum et al. (2013), distributor of subfunc-44 tionsGibson and Goldberg (2009), safeguard against extinctionCrow and Wagner (2005), or merely a 45 passive passengerKimura (1991) remains more an open question. However, evolutionary histories 46 are rife with duplication events, from single genes to whole genomes, and there is some consensus 47 109 site changes the interaction strength by two increments, affecting both the location of the point 110 mutation and the counter-aligned bit. This property of symmetric homomeric interactions is not 111 unique to polyomino models, with greater variance in interaction energetics preferring symmetric 112 homomeric formation extremely generallyLukatsky et al. (2007); Lukatsky and Shakhnovich (2008). 113 The simplicity of binary string binding sites allows the formation rates of both symmetric 114 homomeric and heteromeric interactions to be calculated analytically. The formation of interactions 115 is modelled by an absorbing Markov chain of interaction strengths, randomly walking below the 116 strength threshold. Point mutations correspond to stepping to adjacent strength states. Symmetric 117 homomeric interactions, which can only increment by two states, can be mapped to an equivalent 118 3 of 16 497 Greenbury S, Johnston I, Louis A, Ahnert S. A trac...

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“…The three critical kinetochore linker proteins CENP-C Mif2 , CENP-T Cnn1 , and CENP-U Ame1, are often lost or significantly diverged during evolution. In spite of the observed loss or significant divergence of the protein sequence, other molecular innovations of proteins to link centromeric chromatin to the outer kinetochore, ensuring accurate kinetochore-microtubule interactions remain largely unknown 22, 40, 43 .…”

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confidence: 99%

Identification of bridgin, an unconventional linker, connects the outer kinetochore to centromeric chromatin

Sridhar

Hori

Nakagawa

et al. 2019

Preprint

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1The microtubule-binding outer kinetochore is linked to centromeric chromatin through the inner 2 kinetochore CENP-C Mif2 , CENP-T Cnn1 , and CENP-U Ame1 pathways. These are the only known 3 kinetochore linker proteins across eukaryotes. Linker proteins are structurally less conserved than 4 their outer kinetochore counterparts. Here, we demonstrate the recurrent loss of most inner 5 kinetochore CCAN, including certain linker proteins during evolution in the fungal phylum of 6 Basidiomycota. By studying the kinetochore interactome, a previously undescribed linker protein, 7 bridgin was identified in the basidiomycete Cryptococcus neoformans, a human fungal pathogen. In 8 vivo and in vitro functional analyses of bridgin reveal that it binds to the outer kinetochore and 9 centromere chromatin simultaneously to ensure accurate kinetochore-microtubule attachments. 10Unlike known linker proteins, bridgin is recruited by the outer kinetochore. Homologs of bridgin were 11 identified outside fungi. These results showcase a divergent strategy, with a more ancient origin than 12 fungi, to link the outer kinetochore to centromeric chromatin. 13 14 15 16 17 18 19 20 21 22 23 24 253 Accurate chromosome segregation ensures faithful transmission of the genetic material to the 1 progeny. The kinetochore is a multi-complex protein network that assembles on the centromere of 2 each chromosome 1-4 and is attached to the spindle microtubules for accurate chromosome 3 segregation 5 . Components involved in error correction mechanisms and the spindle assembly 4 checkpoint (SAC) are recruited at kinetochores to ensure bi-orientation of sister chromatids in 5 mitosis 6-9 . The inner kinetochore is composed of CENP-A 10-12 (centromeric Histone H3 variant) and 6 the 16-member (in vertebrates) constitutive centromere associated network (CCAN) [13][14][15][16] . The outer 7 kinetochore members of the KMN (KNL1, Mis12, and Ndc80 complexes) network 1,17 are recruited to 8 CCAN to form the kinetochore ensemble in various model systems including budding yeast and 9 vertebrate cells 18 . Additional components such as the three-member Ska1 complex in vertebrates 10 and the 10-member Dam1 complex (Dam1C) in fungi localize to the outer kinetochore to ensure 11 accurate kinetochore-microtubule interactions [19][20][21][22][23][24] . 12The Ndc80 complex (Ndc80C) of the KMN network directly binds to spindle microtubules [25][26][27] . CCAN 13 proteins, CENP-C Mif2 , and CENP-T Cnn1 have been shown to bridge centromeric chromatin with the 14 KMN network independently [28][29][30][31][32] . Additionally, CENP-U Ame1 functions as a linker in budding yeast 33,34 . 15 CENP-C Mif2 and CENP-T Cnn1 , through their amino-termini (N), interact with the Mis12 complex 16 (Mis12C) and the Ndc80C respectively, while their carboxy(C)-termini interact with centromeric 17 chromatin 35-37 . An extended unstructured region separates the N and C termini in both CENP-C Mif2 18and CENP-T Cnn1 . CENP-U Ame1 also binds to Mis12C and CENP-A Cse4 simultaneously to ensure a 19...

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Mosaic origin of the eukaryotic kinetochore

Cited by 86 publications

References 77 publications

Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution

Comparing orthology methods and their performance by recapitulating patterns of eukaryotic genome evolution

Duplication accelerates the evolution of structural complexity in protein quaternary structure

Identification of bridgin, an unconventional linker, connects the outer kinetochore to centromeric chromatin

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