The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs

Imperfect symmetry facilitated the evolution of specificity and high-order stoichiometry in vertebrate hemoglobin

Many proteins form paralogous multimers - molecular complexes in which evolutionarily related proteins are arranged into specific quaternary structures. Little is known about the mechanisms by which they acquired their stoichiometry (the number of total subunits in the complex) and heterospecificity (the preference of subunits for their paralogs rather than other copies of the same protein). Here we use ancestral protein reconstruction and biochemical experiments to study historical increases in stoichiometry and specificity during the evolution of vertebrate hemoglobin (Hb), a α2β2 heterotetramer that evolved from a homodimeric ancestor after a gene duplication. We show that the mechanisms for this evolutionary transition was simple. One hydrophobic substitution in subunit β after the gene duplication was sufficient to cause the ancestral dimer to homotetramerize with high affinity across a new interface. During this same interval, a single-residue deletion in subunit α at the older interface conferred specificity for the heterotetrameric form and the trans-orientation of subunits within it. These sudden transitions in stoichiometry and specificity were possible because the interfaces in Hb are isologous - involving the same surface patch on interacting subunits, rotated 180° relative to each other - but the symmetry is slightly imperfect. This architecture amplifies the impacts of individual mutations on stoichiometry and specificity, especially in higher-order complexes, and allows single substitutions to differentially affect heteromeric vs homomeric interactions. Many multimers are isologous, and symmetry in proteins is always imperfect; our findings therefore suggest that elaborate and specific molecular complexes may often evolve via simple genetic and physical mechanisms.

Mutational biases favor complexity increases in protein interaction networks after gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

Parallel Nonfunctionalization of CK1δ/ε Kinase Ohnologs Following a Whole-Genome Duplication Event

Whole-genome duplication (WGD) followed by speciation allows us to examine the parallel evolution of ohnolog pairs. In the yeast family Saccharomycetaceae, HRR25 is a rare case of repeated ohnolog maintenance. This gene has reverted to a single copy in Saccharomyces cerevisiae where it is now essential, but has been maintained as pairs in at least 7 species post-WGD. In S. cerevisiae, HRR25 encodes the casein kinase 1δ/ε and plays a role in a variety of functions through its kinase activity and protein-protein interactions (PPIs). We hypothesized that the maintenance of duplicated HRR25 ohnologs could be a result of repeated subfunctionalization. We tested this hypothesis through a functional complementation assay in S. cerevisiae, testing all pairwise combinations of 25 orthologs (including 7 ohnolog pairs). Contrary to our expectations, we observed no cases of pair-dependent complementation, which would have supported the subfunctionalization hypothesis. Instead, most post-WGD species have one ohnolog that failed to complement, suggesting their nonfunctionalization or neofunctionalization. The ohnologs incapable of complementation have undergone more rapid protein evolution, lost most PPIs that were observed for their functional counterparts and singletons from post-WGD and non-WGD species, and have nonconserved cellular localization, consistent with their ongoing loss of function. The analysis in Naumovozyma castellii shows that the noncomplementing ohnolog is expressed at a lower level and has become nonessential. Taken together, our results indicate that HRR25 orthologs are undergoing gradual nonfunctionalization.

The fitness cost of spurious phosphorylation

The fidelity of signal transduction requires the binding of regulatory molecules to their cognate targets. However, the crowded cell interior risks off-target interactions between proteins that are functionally unrelated. How such off-target interactions impact fitness is not generally known, but quantifying this is required to understand the constraints faced by cell systems as they evolve. Here, we use the model organism S. cerevisiae to inducibly express tyrosine kinases. Because yeast lacks bona fide tyrosine kinases, most of the resulting tyrosine phosphorylation is spurious. This provides a suitable system to measure the impact of artificial protein interactions on fitness. We engineered 44 yeast strains each expressing a tyrosine kinase, and quantitatively analysed their phosphoproteomes. This analysis resulted in ~30,000 phosphosites mapping to ~3,500 proteins. Examination of the fitness costs in each strain revealed a strong correlation between the number of spurious pY sites and decreased growth. Moreover, the analysis of pY effects on protein structure and on protein function revealed over 1000 pY events that we predict to be deleterious. However, we also find that a large number of the spurious pY sites have a negligible effect on fitness, possibly because of their low stoichiometry. This result is consistent with our evolutionary analyses demonstrating a lack of phosphotyrosine counter-selection in species with bona fide tyrosine kinases. Taken together, our results suggest that, alongside the risk for toxicity, the cell can tolerate a large degree of non-functional crosstalk as interaction networks evolve.

Parallel nonfunctionalization of CK1δ/ε kinase ohnologs following a whole-genome duplication event

Whole genome duplication (WGD) followed by speciation allows us to examine the parallel evolution of ohnolog pairs. In the yeast family Saccharomycetaceae, HRR25 is a rare case of repeated ohnolog maintenance. This gene has reverted to a single copy in S. cerevisiae where it is now essential, but has been maintained as pairs in at least 7 species post WGD. In S. cerevisiae, HRR25 encodes the casein kinase (CK) 1δ/ε and plays a role in a variety of functions through its kinase activity and protein-protein interactions (PPIs). We hypothesized that the maintenance of duplicated HRR25 ohnologs could be a result of repeated subfunctionalization. We tested this hypothesis through a functional complementation assay in S. cerevisiae, testing all pairwise combinations of 25 orthologs (including 7 ohnolog pairs). Contrary to our expectations, we observed no cases of pair-dependent complementation, which would have supported the subfunctionalization hypothesis. Instead, most post-WGD species have one ohnolog that failed to complement, suggesting their nonfunctionalization or neofunctionalization. The ohnologs incapable of complementation have undergone more rapid protein evolution, lost most PPIs that were observed for their functional counterparts and singletons from post and non-WGD species, and have non-conserved cellular localization, consistent with their ongoing loss of function. The analysis in N. castelli shows that the non-complementing ohnolog is expressed at a lower level and has become non-essential. Taken together, our results indicate that HRR25 orthologs are undergoing gradual nonfunctionalization.

Newfound Coding Potential of Transcripts Unveils Missing Members of Human Protein Communities

Recent proteogenomic approaches have led to the discovery that regions of the transcriptome previously annotated as non-coding regions [i.e., untranslated regions (UTRs), open reading frames overlapping annotated coding sequences in a different reading frame, and non-coding RNAs] frequently encode proteins, termed alternative proteins (altProts). This suggests that previously identified protein-protein interaction (PPI) networks are partially incomplete because altProts are not present in conventional protein databases. Here, we used the proteogenomic resource OpenProt and a combined spectrum- and peptide-centric analysis for the re-analysis of a high-throughput human network proteomics dataset, thereby revealing the presence of 261 altProts in the network. We found 19 genes encoding both an annotated (reference) and an alternative protein interacting with each other. Of the 117 altProts encoded by pseudogenes, 38 are direct interactors of reference proteins encoded by their respective parental genes. Finally, we experimentally validate several interactions involving altProts. These data improve the blueprints of the human PPI network and suggest functional roles for hundreds of altProts.

Evolutionary trade-off and mutational bias could favor transcriptional over translational divergence within paralog pairs

How changes in the different steps of protein synthesis-transcription, translation and degradation-contribute to differences of protein abundance among genes is not fully understood. There is however accumulating evidence that transcriptional divergence might have a prominent role. Here, we show that yeast paralogous genes are more divergent in transcription than in translation. We explore two causal mechanisms for this predominance of transcriptional divergence: an evolutionary trade-off between the precision and economy of gene expression and a larger mutational target size for transcription. Performing simulations within a minimal model of post-duplication evolution, we find that both mechanisms are consistent with the observed divergence patterns. We also investigate how additional properties of the effects of mutations on gene expression, such as their asymmetry and correlation across levels of regulation, can shape the evolution of paralogs. Our results highlight the importance of fully characterizing the distributions of mutational effects on transcription and translation. They also show how general trade-offs in cellular processes and mutation bias can have far-reaching evolutionary impacts.

Point mutations of homologs as an adaptive solution to the gene loss

Gene loss is common and influences genome evolution trajectories. Multiple adaptive strategies to compensate for gene loss have been observed, including copy number gain of paralogous genes and mutations in genes of the same pathway. By using the Ubl-specific protease 2 (ULP2) eviction model, we identify compensatory mutations in the homologous gene ULP1 by laboratory evolution and find that these mutations are capable of rescuing defects caused by the loss of ULP2. Furthermore, bioinformatics analysis of genomes of yeast gene knockout library and natural yeast isolate datasets suggests that point mutations of a homologous gene might be an additional mechanism to compensate gene loss.

Towards a structurally resolved human protein interaction network

Cellular functions are governed by molecular machines that assemble through protein-protein interactions. Their atomic details are critical to studying their molecular mechanisms. However, fewer than 5% of hundreds of thousands of human protein interactions have been structurally characterized. Here we test the potential and limitations of recent progress in deep-learning methods using AlphaFold2 to predict structures for 65,484 human protein interactions. We show that experiments can orthogonally confirm higher-confidence models. We identify 3,137 high-confidence models, of which 1,371 have no homology to a known structure. We identify interface residues harboring disease mutations, suggesting potential mechanisms for pathogenic variants. Groups of interface phosphorylation sites show patterns of co-regulation across conditions, suggestive of coordinated tuning of multiple protein interactions as signaling responses. Finally, we provide examples of how the predicted binary complexes can be used to build larger assemblies helping to expand our understanding of human cell biology.

A universal sequencing read interpreter

Massively parallel DNA sequencing has led to the rapid growth of highly multiplexed experiments in biology. These experiments produce unique sequencing results that require specific analysis pipelines to decode highly structured reads. However, no versatile framework that interprets sequencing reads to extract their encoded information for downstream biological analysis has been developed. Here, we report INTERSTELLAR (interpretation, scalable transformation, and emulation of large-scale sequencing reads) that decodes data values encoded in theoretically any type of sequencing read and translates them into sequencing reads of another structure of choice. We demonstrated that INTERSTELLAR successfully extracted information from a range of short- and long-read sequencing reads and translated those of single-cell (sc)RNA-seq, scATAC-seq, and spatial transcriptomics to be analyzed by different software tools that have been developed for conceptually the same types of experiments. INTERSTELLAR will greatly facilitate the development of sequencing-based experiments and sharing of data analysis pipelines.

Asymmetrical dose responses shape the evolutionary trade-off between antifungal resistance and nutrient use

Antimicrobial resistance is an emerging threat for public health. The success of resistance mutations depends on the trade-off between the benefits and costs they incur. This trade-off is largely unknown and uncharacterized for antifungals. Here, we systematically measure the effect of all amino acid substitutions in the yeast cytosine deaminase Fcy1, the target of the antifungal 5-fluorocytosine (5-FC, flucytosine). We identify over 900 missense mutations granting resistance to 5-FC, a large fraction of which appear to act through destabilization of the protein. The relationship between 5-FC resistance and growth sustained by cytosine deamination is characterized by a sharp trade-off, such that small gains in resistance universally lead to large losses in canonical enzyme function. We show that this steep relationship can be explained by differences in the dose-response functions of 5-FC and cytosine. Finally, we observe the same trade-off shape for the orthologue of FCY1 in Cryptoccocus neoformans, a human pathogen. Our results provide a powerful resource and platform for interpreting drug target variants in fungal pathogens as well as unprecedented insights into resistance-function trade-offs.

How gene duplication diversifies the landscape of protein oligomeric state and function

Oligomeric proteins are central to cellular life and the duplication and divergence of their genes is a key driver of evolutionary innovations. The duplication of a gene coding for an oligomeric protein has numerous possible outcomes, which motivates questions on the relationship between structural and functional divergence. How do protein oligomeric states diversify after gene duplication? In the simple case of duplication of a homo-oligomeric protein gene, what properties can influence the fate of descendant paralogs toward forming independent homomers or maintaining their interaction as a complex? Furthermore, how are functional innovations associated with the diversification of oligomeric states? Here, we review recent literature and present specific examples in an attempt to illustrate and answer these questions.

Retention of duplicated genes in evolution

Gene duplication is a prevalent phenomenon across the tree of life. The processes that lead to the retention of duplicated genes are not well understood. Functional genomics approaches in model organisms, such as yeast, provide useful tools to test the mechanisms underlying retention with functional redundancy and divergence of duplicated genes, including fates associated with neofunctionalization, subfunctionalization, back-up compensation, and dosage amplification. Duplicated genes may also be retained as a consequence of structural and functional entanglement. Advances in human gene editing have enabled the interrogation of duplicated genes in the human genome, providing new tools to evaluate the relative contributions of each of these factors to duplicate gene retention and the evolution of genome structure.

In vivo, in vitro and in silico: an open space for the development of microbe-based applications of synthetic biology

Living systems are studied using three complementary approaches: living cells, cell-free systems and computer-mediated modelling. Progresses in understanding, allowing researchers to create novel chassis and industrial processes rest on a cycle that combines in vivo, in vitro and in silico studies. This design-build-test-learn iteration loop cycle between experiments and analyses combines together physiology, genetics, biochemistry and bioinformatics in a way that keeps going forward. Because computer-aided approaches are not directly constrained by the material nature of the entities of interest, we illustrate here how this virtuous cycle allows researchers to explore chemistry which is foreign to that present in extant life, from whole chassis to novel metabolic cycles. Particular emphasis is placed on the importance of evolution.

OUP accepted manuscript

Barcode fusion genetics (BFG) utilizes deep sequencing to improve the throughput of protein–protein interaction (PPI) screening in pools. BFG has been implemented in Yeast two-hybrid (Y2H) screens (BFG-Y2H). While Y2H requires test protein pairs to localize in the nucleus for reporter reconstruction, dihydrofolate reductase protein-fragment complementation assay (DHFR-PCA) allows proteins to localize in broader subcellular contexts and proves to be largely orthogonal to Y2H. Here, we implemented BFG to DHFR-PCA (BFG-PCA). This plasmid-based system can leverage ORF collections across model organisms to perform comparative analysis, unlike the original DHFR-PCA that requires yeast genomic integration. The scalability and quality of BFG-PCA were demonstrated by screening human and yeast interactions for >11 000 bait-prey pairs. BFG-PCA showed high-sensitivity and high-specificity for capturing known interactions for both species. BFG-Y2H and BFG-PCA capture distinct sets of PPIs, which can partially be explained based on the domain orientation of the reporter tags. BFG-PCA is a high-throughput protein interaction technology to interrogate binary PPIs that exploits clone collections from any species of interest, expanding the scope of PPI assays.

Analysing the yeast complexome-the Complex Portal rising to the challenge

The EMBL-EBI Complex Portal is a knowledgebase of macromolecular complexes providing persistent stable identifiers. Entries are linked to literature evidence and provide details of complex membership, function, structure and complex-specific Gene Ontology annotations. Data are freely available and downloadable in HUPO-PSI community standards and missing entries can be requested for curation. In collaboration with Saccharomyces Genome Database and UniProt, the yeast complexome, a compendium of all known heteromeric assemblies from the model organism Saccharomyces cerevisiae, was curated. This expansion of knowledge and scope has led to a 50% increase in curated complexes compared to the previously published dataset, CYC2008. The yeast complexome is used as a reference resource for the analysis of complexes from large-scale experiments. Our analysis showed that genes coding for proteins in complexes tend to have more genetic interactions, are co-expressed with more genes, are more multifunctional, localize more often in the nucleus, and are more often involved in nucleic acid-related metabolic processes and processes where large machineries are the predominant functional drivers. A comparison to genetic interactions showed that about 40% of expanded co-complex pairs also have genetic interactions, suggesting strong functional links between complex members.

Expression attenuation as a mechanism of robustness against gene duplication

Gene duplication is ubiquitous and a major driver of phenotypic diversity across the tree of life, but its immediate consequences are not fully understood. Deleterious effects would decrease the probability of retention of duplicates and prevent their contribution to long-term evolution. One possible detrimental effect of duplication is the perturbation of the stoichiometry of protein complexes. Here, we measured the fitness effects of the duplication of 899 essential genes in the budding yeast using high-resolution competition assays. At least 10% of genes caused a fitness disadvantage when duplicated. Intriguingly, the duplication of most protein complex subunits had small to nondetectable effects on fitness, with few exceptions. We selected four complexes with subunits that had an impact on fitness when duplicated and measured the impact of individual gene duplications on their protein-protein interactions. We found that very few duplications affect both fitness and interactions. Furthermore, large complexes such as the 26S proteasome are protected from gene duplication by attenuation of protein abundance. Regulatory mechanisms that maintain the stoichiometric balance of protein complexes may protect from the immediate effects of gene duplication. Our results show that a better understanding of protein regulation and assembly in complexes is required for the refinement of current models of gene duplication.

Development of an activity assay for characterizing deoxyhypusine synthase and its diverse reaction products

Deoxyhypusine synthase transfers an aminobutyl moiety from spermidine to the eukaryotic translation initiation factor 5A (eIF5A) in the first step of eIF5A activation. This exclusive post-translational modification is conserved in all eukaryotes. Activated eIF5A has been shown to be essential for cell proliferation and viability. Recent reports have linked the activation of eIF5A to several human diseases. Deoxyhypusine synthase, which is encoded by a single gene copy in most eukaryotes, was duplicated in several plant lineages during evolution, the copies being repeatedly recruited to pyrrolizidine alkaloid biosynthesis. However, the function of many of these duplicates is unknown. Notably, deoxyhypusine synthase is highly promiscuous and can catalyze various reactions, often of unknown biological relevance. To facilitate in-depth biochemical studies of this enzyme, we report here the development of a simple and robust in vitro enzyme assay. It involves precolumn derivatization of the polyamines taking part in the reaction and avoids the need for the previously used radioactively labeled tracers. The derivatized polyamines are quantified after high-performance liquid chromatography coupled to diode array and fluorescence detectors. By performing kinetic analyses of deoxyhypusine synthase and its paralog from the pyrrolizidine alkaloid-producing plant Senecio vernalis, we demonstrate that the assay unequivocally differentiates the paralogous enzymes. Furthermore, it detects and quantifies, in a single assay, the side reactions that occur in parallel to the main reaction. The presented assay thus provides a detailed biochemical characterization of deoxyhypusine synthase and its paralogs.

Genome-scale molecular principles of mRNA half-life regulation in yeast

Precise control of protein and messenger RNA (mRNA) degradation is essential for cellular metabolism and homeostasis. Controlled and specific degradation of both molecular species necessitates their engagements with the respective degradation machineries; this engagement involves a disordered/unstructured segment of the substrate traversing the degradation tunnel of the machinery and accessing the catalytic sites. However, while molecular factors influencing protein degradation have been extensively explored on a genome scale, and in multiple organisms, such a comprehensive understanding remains missing for mRNAs. Here, we analyzed multiple genome-scale experimental yeast mRNA half-life data in light of experimentally derived mRNA secondary structures and protein binding data, along with high-resolution X-ray crystallographic structures of the RNase machines. Results unraveled a consistent genome-scale trend that mRNAs comprising longer terminal and/or internal unstructured segments have significantly shorter half-lives; the lengths of the 5'-terminal, 3'-terminal, and internal unstructured segments that affect mRNA half-life are compatible with molecular structures of the 5' exo-, 3' exo-, and endoribonuclease machineries. Sequestration into ribonucleoprotein complexes elongates mRNA half-life, presumably by burying ribonuclease engagement sites under oligomeric interfaces. After gene duplication, differences in terminal unstructured lengths, proportions of internal unstructured segments, and oligomerization modes result in significantly altered half-lives of paralogous mRNAs. Side-by-side comparison of molecular principles underlying controlled protein and mRNA degradation in yeast unravels their remarkable mechanistic similarities and suggests how the intrinsic structural features of the two molecular species, at two different levels of the central dogma, regulate their half-lives on genome scale.

A large accessory protein interactome is rewired across environments

To characterize how protein-protein interaction (PPI) networks change, we quantified the relative PPI abundance of 1.6 million protein pairs in the yeast Saccharomyces cerevisiae across nine growth conditions, with replication, for a total of 44 million measurements. Our multi-condition screen identified 13,764 pairwise PPIs, a threefold increase over PPIs identified in one condition. A few 'immutable' PPIs are present across all conditions, while most 'mutable' PPIs are rarely observed. Immutable PPIs aggregate into highly connected 'core' network modules, with most network remodeling occurring within a loosely connected 'accessory' module. Mutable PPIs are less likely to co-express, co-localize, and be explained by simple mass action kinetics, and more likely to contain proteins with intrinsically disordered regions, implying that environment-dependent association and binding is critical to cellular adaptation. Our results show that protein interactomes are larger than previously thought and contain highly dynamic regions that reorganize to drive or respond to cellular changes.

Genetic dissection of the auxin response network

The expansion of gene families during evolution, which can generate functional overlap or specialization among their members, is a characteristic feature of signalling pathways in complex organisms. For example, families of transcriptional activators and repressors mediate responses to the plant hormone auxin. Although these regulators were identified more than 20 years ago, their overlapping functions and compensating negative feedbacks have hampered their functional analyses. Studies using loss-of-function approaches in basal land plants and gain-of-function approaches in angiosperms have in part overcome these issues but have still left an incomplete understanding. Here, we propose that renewed emphasis on genetic analysis of multiple mutants and species will shed light on the role of gene families in auxin response. Combining loss-of-function mutations in auxin-response activators and repressors can unravel complex outputs enabled by expanded gene families, such as fine-tuned developmental outcomes and robustness. Similar approaches and concepts may help to analyse other regulatory pathways whose components are also encoded by large gene families.

Determining the interaction status and evolutionary fate of duplicated homomeric proteins

Oligomeric proteins are central to life. Duplication and divergence of their genes is a key evolutionary driver, also because duplications can yield very different outcomes. Given a homomeric ancestor, duplication can yield two paralogs that form two distinct homomeric complexes, or a heteromeric complex comprising both paralogs. Alternatively, one paralog remains a homomer while the other acquires a new partner. However, so far, conflicting trends have been noted with respect to which fate dominates, primarily because different methods and criteria are being used to assign the interaction status of paralogs. Here, we systematically analyzed all Saccharomyces cerevisiae and Escherichia coli oligomeric complexes that include paralogous proteins. We found that the proportions of homo-hetero duplication fates strongly depend on a variety of factors, yet that nonetheless, rigorous filtering gives a consistent picture. In E. coli about 50%, of the paralogous pairs appear to have retained the ancestral homomeric interaction, whereas in S. cerevisiae only ~10% retained a homomeric state. This difference was also observed when unique complexes were counted instead of paralogous gene pairs. We further show that this difference is accounted for by multiple cases of heteromeric yeast complexes that share common ancestry with homomeric bacterial complexes. Our analysis settles contradicting trends and conflicting previous analyses, and provides a systematic and rigorous pipeline for delineating the fate of duplicated oligomers in any organism for which protein-protein interaction data are available.

About half of all proteins assemble as oligomers, either by self-interaction (homomers) or via interaction with another protein (heteromers). The latter can be unrelated, yet, quite commonly, the interacting proteins are paralogs, namely two genes that arose by gene duplication. Indeed, while a homomer is encoded by a single gene, heteromers demand two genes as a minimum. Duplication can therefore yield two discrete homomeric complexes or a single heteromer. Do paralogs tend to retain the ancestral homomeric interaction, or do they mostly diverge into heteromeric complexes? Despite several studies addressing this question, to date, we lack a systematic, rigorous approach for delineating the oligomeric fates of paralogs on an organism scale. To this end, we developed a new pipeline for analysis of molecular interaction databases that includes various filtering steps and unambiguous definitions of all possible oligomeric fates. Applying this method to Escherichia coli and Saccharomyces cerevisiae we noted that paralogous pairs tend to remain homomeric in the former while in the latter heteromeric complexes dominate. We consequently note a systematic trend of homomeric bacterial proteins diverging into heteromeric complexes in eukaryotes.

Exploring whole-genome duplicate gene retention with complex genetic interaction analysis

Whole-genome duplication has played a central role in the genome evolution of many organisms, including the human genome. Most duplicated genes are eliminated, and factors that influence the retention of persisting duplicates remain poorly understood. We describe a systematic complex genetic interaction analysis with yeast paralogs derived from the whole-genome duplication event. Mapping of digenic interactions for a deletion mutant of each paralog, and of trigenic interactions for the double mutant, provides insight into their roles and a quantitative measure of their functional redundancy. Trigenic interaction analysis distinguishes two classes of paralogs: a more functionally divergent subset and another that retained more functional overlap. Gene feature analysis and modeling suggest that evolutionary trajectories of duplicated genes are dictated by combined functional and structural entanglement factors.

Similarities in biological processes can be used to bridge ecology and molecular biology

Much of the research in biology aims to understand the origin of diversity. Naturally, ecological diversity was the first object of study, but we now have the necessary tools to probe diversity at molecular scales. The inherent differences in how we study diversity at different scales caused the disciplines of biology to be organized around these levels, from molecular biology to ecology. Here, we illustrate that there are key properties of each scale that emerge from the interactions of simpler components and that these properties are often shared across different levels of organization. This means that ideas from one level of organization can be an inspiration for novel hypotheses to study phenomena at another level. We illustrate this concept with examples of events at the molecular level that have analogs at the organismal or ecological level and vice versa. Through these examples, we illustrate that biological processes at different organization levels are governed by general rules. The study of the same phenomena at different scales could enrich our work through a multidisciplinary approach, which should be a staple in the training of future scientists.

Coevolutionary Analysis of Protein Subfamilies by Sequence Reweighting

Extracting structural information from sequence co-variation has become a common computational biology practice in the recent years, mainly due to the availability of large sequence alignments of protein families. However, identifying features that are specific to sub-classes and not shared by all members of the family using sequence-based approaches has remained an elusive problem. We here present a coevolutionary-based method to differentially analyze subfamily specific structural features by a continuous sequence reweighting (SR) approach. We introduce the underlying principles and test its predictive capabilities on the Response Regulator family, whose subfamilies have been previously shown to display distinct, specific homo-dimerization patterns. Our results show that this reweighting scheme is effective in assigning structural features known a priori to subfamilies, even when sequence data is relatively scarce. Furthermore, sequence reweighting allows assessing if individual structural contacts pertain to specific subfamilies and it thus paves the way for the identification specificity-determining contacts from sequence variation data.